diff --git a/doc/xgboost_on_sqlflow_design.md b/doc/ant-xgboost_on_sqlflow_design.md
similarity index 97%
rename from doc/xgboost_on_sqlflow_design.md
rename to doc/ant-xgboost_on_sqlflow_design.md
index b8bdd9d0b1..c7b8c6eb94 100644
--- a/doc/xgboost_on_sqlflow_design.md
+++ b/doc/ant-xgboost_on_sqlflow_design.md
@@ -1,8 +1,8 @@
-# _Design:_ xgboost on sqlflow
+# _Design:_ ant-xgboost on sqlflow
 
 ## Overview
 
-This is a design doc about why and how to support running xgboost via sqlflow as a machine learning estimator.
+This is a design doc about why and how to support running ant-xgboost via sqlflow as a machine learning estimator.
 
 We propose to build a lightweight python template for xgboost on basis of `xgblauncher`,
 an incubating xgboost wrapper in [ant-xgboost](https://github.com/alipay/ant-xgboost).
diff --git a/scripts/test_e2e.sh b/scripts/test_e2e.sh
index 194fa4a11a..47646d1202 100644
--- a/scripts/test_e2e.sh
+++ b/scripts/test_e2e.sh
@@ -48,8 +48,8 @@ export PYTHONPATH=$GOPATH/src/github.com/sql-machine-learning/sqlflow/sql/python
 sqlflowserver --datasource=${DATASOURCE} &
 # e2e test for standard SQL
 SQLFLOW_SERVER=localhost:50051 ipython sql/python/test_magic.py
-# e2e test for xgboost train and prediciton SQL.
-SQLFLOW_SERVER=localhost:50051 ipython sql/python/test_magic_xgboost.py
+# e2e test for ant-xgboost train and prediciton SQL.
+SQLFLOW_SERVER=localhost:50051 ipython sql/python/test_magic_ant_xgboost.py
 # TODO(terrytangyuan): Enable this when ElasticDL is open sourced
 # e2e test for ElasticDL SQL
 # export SQLFLOW_submitter=elasticdl
diff --git a/sql/codegen_analyze.go b/sql/codegen_analyze.go
index a73c44015a..bd609c023a 100644
--- a/sql/codegen_analyze.go
+++ b/sql/codegen_analyze.go
@@ -41,7 +41,7 @@ func readFeatureNames(pr *extendedSelect, db *DB) ([]string, string, error) {
 	if strings.HasPrefix(strings.ToUpper(pr.estimator), `XGBOOST.`) {
 		// TODO(weiguo): It's a quick way to read column and label names from
 		// xgboost.*, but too heavy.
-		xgbFiller, err := newXGBoostFiller(pr, nil, db)
+		xgbFiller, err := newAntXGBoostFiller(pr, nil, db)
 		if err != nil {
 			return nil, "", err
 		}
diff --git a/sql/codegen_xgboost.go b/sql/codegen_ant_xgboost.go
similarity index 85%
rename from sql/codegen_xgboost.go
rename to sql/codegen_ant_xgboost.go
index 0dd54000d0..52c57a516e 100644
--- a/sql/codegen_xgboost.go
+++ b/sql/codegen_ant_xgboost.go
@@ -28,7 +28,7 @@ import (
 	"sqlflow.org/gomaxcompute"
 )
 
-type xgboostFiller struct {
+type antXGBoostFiller struct {
 	ModelPath string
 	xgLearningFields
 	xgColumnFields
@@ -164,15 +164,15 @@ func xgMultiSparseError(colNames []string) error {
 }
 
 func xgUnknownFCError(kw string) error {
-	return fmt.Errorf("xgUnknownFCError: feature column keyword(`%s`) is not supported by xgboost engine", kw)
+	return fmt.Errorf("xgUnknownFCError: feature column keyword(`%s`) is not supported by ant-xgboost engine", kw)
 }
 
 func xgUnsupportedColTagError() error {
-	return fmt.Errorf("xgUnsupportedColTagError: valid column tags of xgboost engine([feature_columns, group, weight])")
+	return fmt.Errorf("xgUnsupportedColTagError: valid column tags of ant-xgboost engine([feature_columns, group, weight])")
 }
 
-func uIntPartial(key string, ptrFn func(*xgboostFiller) *uint) func(*map[string][]string, *xgboostFiller) error {
-	return func(a *map[string][]string, r *xgboostFiller) error {
+func uIntPartial(key string, ptrFn func(*antXGBoostFiller) *uint) func(*map[string][]string, *antXGBoostFiller) error {
+	return func(a *map[string][]string, r *antXGBoostFiller) error {
 		// xgParseAttr will ensure the key is existing in map
 		val, _ := (*a)[key]
 		if len(val) != 1 {
@@ -190,8 +190,8 @@ func uIntPartial(key string, ptrFn func(*xgboostFiller) *uint) func(*map[string]
 	}
 }
 
-func fp32Partial(key string, ptrFn func(*xgboostFiller) *float32) func(*map[string][]string, *xgboostFiller) error {
-	return func(a *map[string][]string, r *xgboostFiller) error {
+func fp32Partial(key string, ptrFn func(*antXGBoostFiller) *float32) func(*map[string][]string, *antXGBoostFiller) error {
+	return func(a *map[string][]string, r *antXGBoostFiller) error {
 		// xgParseAttr will ensure the key is existing in map
 		val, _ := (*a)[key]
 		if len(val) != 1 {
@@ -209,8 +209,8 @@ func fp32Partial(key string, ptrFn func(*xgboostFiller) *float32) func(*map[stri
 	}
 }
 
-func boolPartial(key string, ptrFn func(*xgboostFiller) *bool) func(*map[string][]string, *xgboostFiller) error {
-	return func(a *map[string][]string, r *xgboostFiller) error {
+func boolPartial(key string, ptrFn func(*antXGBoostFiller) *bool) func(*map[string][]string, *antXGBoostFiller) error {
+	return func(a *map[string][]string, r *antXGBoostFiller) error {
 		// xgParseAttr will ensure the key is existing in map
 		val, _ := (*a)[key]
 		if len(val) != 1 {
@@ -227,8 +227,8 @@ func boolPartial(key string, ptrFn func(*xgboostFiller) *bool) func(*map[string]
 	}
 }
 
-func strPartial(key string, ptrFn func(*xgboostFiller) *string) func(*map[string][]string, *xgboostFiller) error {
-	return func(a *map[string][]string, r *xgboostFiller) error {
+func strPartial(key string, ptrFn func(*antXGBoostFiller) *string) func(*map[string][]string, *antXGBoostFiller) error {
+	return func(a *map[string][]string, r *antXGBoostFiller) error {
 		// xgParseAttr will ensure the key is existing in map
 		val, _ := (*a)[key]
 		if len(val) != 1 {
@@ -244,8 +244,8 @@ func strPartial(key string, ptrFn func(*xgboostFiller) *string) func(*map[string
 	}
 }
 
-func sListPartial(key string, ptrFn func(*xgboostFiller) *[]string) func(*map[string][]string, *xgboostFiller) error {
-	return func(a *map[string][]string, r *xgboostFiller) error {
+func sListPartial(key string, ptrFn func(*antXGBoostFiller) *[]string) func(*map[string][]string, *antXGBoostFiller) error {
+	return func(a *map[string][]string, r *antXGBoostFiller) error {
 		// xgParseAttr will ensure the key is existing in map
 		val, _ := (*a)[key]
 		strListPtr := ptrFn(r)
@@ -258,48 +258,48 @@ func sListPartial(key string, ptrFn func(*xgboostFiller) *[]string) func(*map[st
 	}
 }
 
-var xgbTrainAttrSetterMap = map[string]func(*map[string][]string, *xgboostFiller) error{
+var xgbTrainAttrSetterMap = map[string]func(*map[string][]string, *antXGBoostFiller) error{
 	// booster params
-	"train.objective":            strPartial("train.objective", func(r *xgboostFiller) *string { return &(r.Objective) }),
-	"train.eval_metric":          strPartial("train.eval_metric", func(r *xgboostFiller) *string { return &(r.EvalMetric) }),
-	"train.booster":              strPartial("train.booster", func(r *xgboostFiller) *string { return &(r.Booster) }),
-	"train.seed":                 uIntPartial("train.seed", func(r *xgboostFiller) *uint { return &(r.Seed) }),
-	"train.num_class":            uIntPartial("train.num_class", func(r *xgboostFiller) *uint { return &(r.NumClass) }),
-	"train.eta":                  fp32Partial("train.eta", func(r *xgboostFiller) *float32 { return &(r.Eta) }),
-	"train.gamma":                fp32Partial("train.gamma", func(r *xgboostFiller) *float32 { return &(r.Gamma) }),
-	"train.max_depth":            uIntPartial("train.max_depth", func(r *xgboostFiller) *uint { return &(r.MaxDepth) }),
-	"train.min_child_weight":     uIntPartial("train.min_child_weight", func(r *xgboostFiller) *uint { return &(r.MinChildWeight) }),
-	"train.subsample":            fp32Partial("train.subsample", func(r *xgboostFiller) *float32 { return &(r.Subsample) }),
-	"train.colsample_bytree":     fp32Partial("train.colsample_bytree", func(r *xgboostFiller) *float32 { return &(r.ColSampleByTree) }),
-	"train.colsample_bylevel":    fp32Partial("train.colsample_bylevel", func(r *xgboostFiller) *float32 { return &(r.ColSampleByLevel) }),
-	"train.colsample_bynode":     fp32Partial("train.colsample_bynode", func(r *xgboostFiller) *float32 { return &(r.ColSampleByNode) }),
-	"train.lambda":               fp32Partial("train.lambda", func(r *xgboostFiller) *float32 { return &(r.Lambda) }),
-	"train.alpha":                fp32Partial("train.alpha", func(r *xgboostFiller) *float32 { return &(r.Alpha) }),
-	"train.tree_method":          strPartial("train.tree_method", func(r *xgboostFiller) *string { return &(r.TreeMethod) }),
-	"train.sketch_eps":           fp32Partial("train.sketch_eps", func(r *xgboostFiller) *float32 { return &(r.SketchEps) }),
-	"train.scale_pos_weight":     fp32Partial("train.scale_pos_weight", func(r *xgboostFiller) *float32 { return &(r.ScalePosWeight) }),
-	"train.grow_policy":          strPartial("train.grow_policy", func(r *xgboostFiller) *string { return &(r.GrowPolicy) }),
-	"train.max_leaves":           uIntPartial("train.max_leaves", func(r *xgboostFiller) *uint { return &(r.MaxLeaves) }),
-	"train.max_bin":              uIntPartial("train.max_bin", func(r *xgboostFiller) *uint { return &(r.MaxBin) }),
-	"train.num_parallel_tree":    uIntPartial("train.num_parallel_tree", func(r *xgboostFiller) *uint { return &(r.NumParallelTree) }),
-	"train.convergence_criteria": strPartial("train.convergence_criteria", func(r *xgboostFiller) *string { return &(r.ConvergenceCriteria) }),
-	"train.verbosity":            uIntPartial("train.verbosity", func(r *xgboostFiller) *uint { return &(r.Verbosity) }),
+	"train.objective":            strPartial("train.objective", func(r *antXGBoostFiller) *string { return &(r.Objective) }),
+	"train.eval_metric":          strPartial("train.eval_metric", func(r *antXGBoostFiller) *string { return &(r.EvalMetric) }),
+	"train.booster":              strPartial("train.booster", func(r *antXGBoostFiller) *string { return &(r.Booster) }),
+	"train.seed":                 uIntPartial("train.seed", func(r *antXGBoostFiller) *uint { return &(r.Seed) }),
+	"train.num_class":            uIntPartial("train.num_class", func(r *antXGBoostFiller) *uint { return &(r.NumClass) }),
+	"train.eta":                  fp32Partial("train.eta", func(r *antXGBoostFiller) *float32 { return &(r.Eta) }),
+	"train.gamma":                fp32Partial("train.gamma", func(r *antXGBoostFiller) *float32 { return &(r.Gamma) }),
+	"train.max_depth":            uIntPartial("train.max_depth", func(r *antXGBoostFiller) *uint { return &(r.MaxDepth) }),
+	"train.min_child_weight":     uIntPartial("train.min_child_weight", func(r *antXGBoostFiller) *uint { return &(r.MinChildWeight) }),
+	"train.subsample":            fp32Partial("train.subsample", func(r *antXGBoostFiller) *float32 { return &(r.Subsample) }),
+	"train.colsample_bytree":     fp32Partial("train.colsample_bytree", func(r *antXGBoostFiller) *float32 { return &(r.ColSampleByTree) }),
+	"train.colsample_bylevel":    fp32Partial("train.colsample_bylevel", func(r *antXGBoostFiller) *float32 { return &(r.ColSampleByLevel) }),
+	"train.colsample_bynode":     fp32Partial("train.colsample_bynode", func(r *antXGBoostFiller) *float32 { return &(r.ColSampleByNode) }),
+	"train.lambda":               fp32Partial("train.lambda", func(r *antXGBoostFiller) *float32 { return &(r.Lambda) }),
+	"train.alpha":                fp32Partial("train.alpha", func(r *antXGBoostFiller) *float32 { return &(r.Alpha) }),
+	"train.tree_method":          strPartial("train.tree_method", func(r *antXGBoostFiller) *string { return &(r.TreeMethod) }),
+	"train.sketch_eps":           fp32Partial("train.sketch_eps", func(r *antXGBoostFiller) *float32 { return &(r.SketchEps) }),
+	"train.scale_pos_weight":     fp32Partial("train.scale_pos_weight", func(r *antXGBoostFiller) *float32 { return &(r.ScalePosWeight) }),
+	"train.grow_policy":          strPartial("train.grow_policy", func(r *antXGBoostFiller) *string { return &(r.GrowPolicy) }),
+	"train.max_leaves":           uIntPartial("train.max_leaves", func(r *antXGBoostFiller) *uint { return &(r.MaxLeaves) }),
+	"train.max_bin":              uIntPartial("train.max_bin", func(r *antXGBoostFiller) *uint { return &(r.MaxBin) }),
+	"train.num_parallel_tree":    uIntPartial("train.num_parallel_tree", func(r *antXGBoostFiller) *uint { return &(r.NumParallelTree) }),
+	"train.convergence_criteria": strPartial("train.convergence_criteria", func(r *antXGBoostFiller) *string { return &(r.ConvergenceCriteria) }),
+	"train.verbosity":            uIntPartial("train.verbosity", func(r *antXGBoostFiller) *uint { return &(r.Verbosity) }),
 	// xgboost train controllers
-	"train.num_round":  uIntPartial("train.num_round", func(r *xgboostFiller) *uint { return &(r.NumRound) }),
-	"train.auto_train": boolPartial("train.auto_train", func(r *xgboostFiller) *bool { return &(r.AutoTrain) }),
+	"train.num_round":  uIntPartial("train.num_round", func(r *antXGBoostFiller) *uint { return &(r.NumRound) }),
+	"train.auto_train": boolPartial("train.auto_train", func(r *antXGBoostFiller) *bool { return &(r.AutoTrain) }),
 	// Label, Group, Weight and xgFeatureFields are parsed from columnClause
 }
 
-var xgbPredAttrSetterMap = map[string]func(*map[string][]string, *xgboostFiller) error{
+var xgbPredAttrSetterMap = map[string]func(*map[string][]string, *antXGBoostFiller) error{
 	// xgboost output columns (for prediction)
-	"pred.append_columns":  sListPartial("pred.append_columns", func(r *xgboostFiller) *[]string { return &(r.AppendColumns) }),
-	"pred.prob_column":     strPartial("pred.prob_column", func(r *xgboostFiller) *string { return &(r.ProbColumn) }),
-	"pred.detail_column":   strPartial("pred.detail_column", func(r *xgboostFiller) *string { return &(r.DetailColumn) }),
-	"pred.encoding_column": strPartial("pred.encoding_column", func(r *xgboostFiller) *string { return &(r.EncodingColumn) }),
+	"pred.append_columns":  sListPartial("pred.append_columns", func(r *antXGBoostFiller) *[]string { return &(r.AppendColumns) }),
+	"pred.prob_column":     strPartial("pred.prob_column", func(r *antXGBoostFiller) *string { return &(r.ProbColumn) }),
+	"pred.detail_column":   strPartial("pred.detail_column", func(r *antXGBoostFiller) *string { return &(r.DetailColumn) }),
+	"pred.encoding_column": strPartial("pred.encoding_column", func(r *antXGBoostFiller) *string { return &(r.EncodingColumn) }),
 	// Label, Group, Weight and xgFeatureFields are parsed from columnClause
 }
 
-func xgParseAttr(pr *extendedSelect, r *xgboostFiller) error {
+func xgParseAttr(pr *extendedSelect, r *antXGBoostFiller) error {
 	var rawAttrs map[string]*expr
 	if pr.train {
 		rawAttrs = pr.trainAttrs
@@ -324,8 +324,8 @@ func xgParseAttr(pr *extendedSelect, r *xgboostFiller) error {
 		}
 	}
 
-	// fill xgboostFiller with attrs
-	var setterMap map[string]func(*map[string][]string, *xgboostFiller) error
+	// fill antXGBoostFiller with attrs
+	var setterMap map[string]func(*map[string][]string, *antXGBoostFiller) error
 	if pr.train {
 		setterMap = xgbTrainAttrSetterMap
 	} else {
@@ -358,7 +358,7 @@ func xgParseAttr(pr *extendedSelect, r *xgboostFiller) error {
 //		data example: COLUMN SPARSE("0:1.5 1:100.1f 11:-1.2", [20], " ")
 //	2. tf feature columns
 //		Roughly same as TFEstimator, except output shape of feaColumns are required to be 1-dim.
-func parseFeatureColumns(columns *exprlist, r *xgboostFiller) error {
+func parseFeatureColumns(columns *exprlist, r *antXGBoostFiller) error {
 	feaCols, colSpecs, err := resolveTrainColumns(columns)
 	if err != nil {
 		return err
@@ -379,7 +379,7 @@ func parseFeatureColumns(columns *exprlist, r *xgboostFiller) error {
 
 // parseSparseKeyValueFeatures, parse features which is identified by `SPARSE`.
 // ex: SPARSE(col1, [100], comma)
-func parseSparseKeyValueFeatures(colSpecs []*columnSpec, r *xgboostFiller) error {
+func parseSparseKeyValueFeatures(colSpecs []*columnSpec, r *antXGBoostFiller) error {
 	var colNames []string
 	for _, spec := range colSpecs {
 		colNames = append(colNames, spec.ColumnName)
@@ -425,7 +425,7 @@ func isSimpleColumn(col featureColumn) bool {
 	return false
 }
 
-func parseDenseFeatures(feaCols []featureColumn, r *xgboostFiller) error {
+func parseDenseFeatures(feaCols []featureColumn, r *antXGBoostFiller) error {
 	allSimpleCol := true
 	for _, col := range feaCols {
 		if allSimpleCol && !isSimpleColumn(col) {
@@ -511,7 +511,7 @@ func parseSimpleColumn(field string, columns *exprlist) (*xgFeatureMeta, error)
 	return fm, nil
 }
 
-func xgParseColumns(pr *extendedSelect, filler *xgboostFiller) error {
+func xgParseColumns(pr *extendedSelect, filler *antXGBoostFiller) error {
 	for target, columns := range pr.columns {
 		switch target {
 		case "feature_columns":
@@ -553,7 +553,7 @@ func xgParseColumns(pr *extendedSelect, filler *xgboostFiller) error {
 	return nil
 }
 
-func xgParseEstimator(pr *extendedSelect, filler *xgboostFiller) error {
+func xgParseEstimator(pr *extendedSelect, filler *antXGBoostFiller) error {
 	switch strings.ToUpper(pr.estimator) {
 	case "XGBOOST.ESTIMATOR":
 		if len(filler.Objective) == 0 {
@@ -590,8 +590,8 @@ func xgParseEstimator(pr *extendedSelect, filler *xgboostFiller) error {
 	return nil
 }
 
-func newXGBoostFiller(pr *extendedSelect, ds *trainAndValDataset, db *DB) (*xgboostFiller, error) {
-	filler := &xgboostFiller{
+func newAntXGBoostFiller(pr *extendedSelect, ds *trainAndValDataset, db *DB) (*antXGBoostFiller, error) {
+	filler := &antXGBoostFiller{
 		ModelPath: pr.save,
 	}
 	filler.IsTrain = pr.train
@@ -720,7 +720,7 @@ func xgFillDatabaseInfo(r *xgDataSourceFields, db *DB) error {
 	return nil
 }
 
-func xgCreatePredictionTable(pr *extendedSelect, r *xgboostFiller, db *DB) error {
+func xgCreatePredictionTable(pr *extendedSelect, r *antXGBoostFiller, db *DB) error {
 	dropStmt := fmt.Sprintf("drop table if exists %s;", r.OutputTable)
 	if _, e := db.Exec(dropStmt); e != nil {
 		return fmt.Errorf("failed executing %s: %q", dropStmt, e)
@@ -791,7 +791,7 @@ func xgCreatePredictionTable(pr *extendedSelect, r *xgboostFiller, db *DB) error
 }
 
 func genXG(w io.Writer, pr *extendedSelect, ds *trainAndValDataset, fts fieldTypes, db *DB) error {
-	r, e := newXGBoostFiller(pr, ds, db)
+	r, e := newAntXGBoostFiller(pr, ds, db)
 	if e != nil {
 		return e
 	}
@@ -808,7 +808,7 @@ var xgTemplate = template.Must(template.New("codegenXG").Parse(xgTemplateText))
 
 const xgTemplateText = `
 from launcher.config_fields import JobType
-from sqlflow_submitter.xgboost import run_with_sqlflow
+from sqlflow_submitter.ant_xgboost import run_with_sqlflow
 
 {{if .IsTrain}}
 mode = JobType.TRAIN
diff --git a/sql/codegen_xgboost_test.go b/sql/codegen_ant_xgboost_test.go
similarity index 92%
rename from sql/codegen_xgboost_test.go
rename to sql/codegen_ant_xgboost_test.go
index 34e8bc4033..665de64e55 100644
--- a/sql/codegen_xgboost_test.go
+++ b/sql/codegen_ant_xgboost_test.go
@@ -22,7 +22,7 @@ import (
 )
 
 const (
-	testXGTrainSelectIris = `
+	testAntXGTrainSelectIris = `
 SELECT *
 FROM iris.train
 TRAIN xgboost.Estimator
@@ -36,13 +36,13 @@ WITH
 COLUMN sepal_length, sepal_width, petal_length, petal_width
 LABEL class INTO sqlflow_models.my_xgboost_model;
 `
-	testXGAnalyzeSelectIris = `
+	testAntXGAnalyzeSelectIris = `
 SELECT *
 FROM iris.train
 ANALYZE sqlflow_models.my_xgboost_model
 USING TreeExplainer;
 	`
-	testXGPredSelectIris = `
+	testAntXGPredSelectIris = `
 SELECT *
 FROM iris.test
 PREDICT iris.predict.result
@@ -57,10 +57,10 @@ USING sqlflow_models.my_xgboost_model;
 func TestPartials(t *testing.T) {
 	a := assert.New(t)
 	tmpMap := make(map[string][]string)
-	filler := &xgboostFiller{}
+	filler := &antXGBoostFiller{}
 
 	// test strPartial
-	part := strPartial("obj", func(r *xgboostFiller) *string { return &(r.Objective) })
+	part := strPartial("obj", func(r *antXGBoostFiller) *string { return &(r.Objective) })
 	tmpMap["obj"] = []string{"binary:logistic"}
 	e := part(&tmpMap, filler)
 	a.NoError(e)
@@ -83,7 +83,7 @@ func TestPartials(t *testing.T) {
 	a.Equal(filler.Objective, "reg:squarederror")
 
 	// test uIntPartial
-	part = uIntPartial("num_class", func(r *xgboostFiller) *uint { return &(r.NumClass) })
+	part = uIntPartial("num_class", func(r *antXGBoostFiller) *uint { return &(r.NumClass) })
 	tmpMap["num_class"] = []string{"3"}
 	e = part(&tmpMap, filler)
 	a.NoError(e)
@@ -92,7 +92,7 @@ func TestPartials(t *testing.T) {
 	a.Equal(ok, false)
 
 	// test fp32Partial
-	part = fp32Partial("eta", func(r *xgboostFiller) *float32 { return &(r.Eta) })
+	part = fp32Partial("eta", func(r *antXGBoostFiller) *float32 { return &(r.Eta) })
 	tmpMap["eta"] = []string{"-0.33"}
 	e = part(&tmpMap, filler)
 	a.NoError(e)
@@ -101,7 +101,7 @@ func TestPartials(t *testing.T) {
 	a.Equal(ok, false)
 
 	// test boolPartial
-	part = boolPartial("auto_train", func(r *xgboostFiller) *bool { return &(r.AutoTrain) })
+	part = boolPartial("auto_train", func(r *antXGBoostFiller) *bool { return &(r.AutoTrain) })
 	tmpMap["auto_train"] = []string{"false"}
 	e = part(&tmpMap, filler)
 	a.NoError(e)
@@ -114,7 +114,7 @@ func TestPartials(t *testing.T) {
 	a.Equal(filler.AutoTrain, true)
 
 	// test sListPartial
-	part = sListPartial("append_columns", func(r *xgboostFiller) *[]string { return &(r.AppendColumns) })
+	part = sListPartial("append_columns", func(r *antXGBoostFiller) *[]string { return &(r.AppendColumns) })
 	tmpMap["append_columns"] = []string{"AA", "BB", "CC"}
 	e = part(&tmpMap, filler)
 	a.NoError(e)
@@ -131,8 +131,8 @@ func TestXGBoostAttr(t *testing.T) {
 	}
 	parser := newParser()
 
-	parseAndFill := func(clause string) *xgboostFiller {
-		filler := &xgboostFiller{}
+	parseAndFill := func(clause string) *antXGBoostFiller {
+		filler := &antXGBoostFiller{}
 		r, e := parser.Parse(clause)
 		a.NoError(e)
 		e = xgParseAttr(r, filler)
@@ -235,7 +235,7 @@ WITH attr_x = XXX
 LABEL e INTO model_table;
 `
 	// test sparseKV schema
-	filler := &xgboostFiller{}
+	filler := &antXGBoostFiller{}
 	sparseKVSpec := ` COLUMN SPARSE(a, 100, comma) `
 	r, e := parser.Parse(sqlHead + sparseKVSpec + sqlTail)
 	a.NoError(e)
@@ -256,7 +256,7 @@ LABEL e INTO model_table;
 	a.EqualValues("e", filler.Label)
 
 	// test raw columns
-	filler = &xgboostFiller{}
+	filler = &antXGBoostFiller{}
 	rawColumnsSpec := " COLUMN a, b, b, c, d, c "
 	r, _ = parser.Parse(sqlHead + rawColumnsSpec + sqlTail)
 	e = xgParseColumns(r, filler)
@@ -277,7 +277,7 @@ LABEL e INTO model_table;
 	}
 
 	// test tf.feature_columns
-	filler = &xgboostFiller{}
+	filler = &antXGBoostFiller{}
 	fcSpec := " COLUMN a, b, c, EMBEDDING(CATEGORY_ID(d, 2000), 8, mean) FOR feature_columns "
 	r, _ = parser.Parse(sqlHead + fcSpec + sqlTail)
 	e = xgParseColumns(r, filler)
@@ -288,7 +288,7 @@ LABEL e INTO model_table;
 	a.True(filler.IsTensorFlowIntegrated)
 
 	// test group & weight
-	filler = &xgboostFiller{}
+	filler = &antXGBoostFiller{}
 	groupWeightSpec := " COLUMN gg FOR group COLUMN ww FOR weight "
 	r, _ = parser.Parse(sqlHead + fcSpec + groupWeightSpec + sqlTail)
 	e = xgParseColumns(r, filler)
@@ -299,7 +299,7 @@ LABEL e INTO model_table;
 	a.EqualValues("ww", filler.Weight)
 
 	// test xgMixSchemaError
-	filler = &xgboostFiller{}
+	filler = &antXGBoostFiller{}
 	wrongColSpec := " COLUMN SPARSE(a, 2000, comma), b, c, d "
 	r, _ = parser.Parse(sqlHead + wrongColSpec + sqlTail)
 	e = xgParseColumns(r, filler)
@@ -307,7 +307,7 @@ LABEL e INTO model_table;
 	a.EqualValues(e, xgParseColumnError("feature_columns", xgMixSchemaError()))
 
 	// test `DENSE` keyword
-	filler = &xgboostFiller{}
+	filler = &antXGBoostFiller{}
 	wrongColSpec = " COLUMN DENSE(b, 5, comma) "
 	r, _ = parser.Parse(sqlHead + wrongColSpec + sqlTail)
 	e = xgParseColumns(r, filler)
@@ -315,7 +315,7 @@ LABEL e INTO model_table;
 	a.EqualValues(e, xgParseColumnError("feature_columns", xgUnknownFCError("DENSE")))
 
 	// test xgMultiSparseError
-	filler = &xgboostFiller{}
+	filler = &antXGBoostFiller{}
 	wrongColSpec = " COLUMN SPARSE(a, 2000, comma), SPARSE(b, 100, comma) "
 	r, _ = parser.Parse(sqlHead + wrongColSpec + sqlTail)
 	e = xgParseColumns(r, filler)
@@ -323,7 +323,7 @@ LABEL e INTO model_table;
 	a.EqualValues(e, xgParseColumnError("feature_columns", xgMultiSparseError([]string{"a", "b"})))
 
 	// test xgUnsupportedColTagError
-	filler = &xgboostFiller{}
+	filler = &antXGBoostFiller{}
 	unsupportedSpec := " COLUMN gg FOR group COLUMN ww FOR xxxxx "
 	r, _ = parser.Parse(sqlHead + fcSpec + unsupportedSpec + sqlTail)
 	e = xgParseColumns(r, filler)
@@ -350,7 +350,7 @@ LABEL e INTO model_table;
 `
 	pr, e := parser.Parse(trainClause)
 	a.NoError(e)
-	filler, e := newXGBoostFiller(pr, nil, testDB)
+	filler, e := newAntXGBoostFiller(pr, nil, testDB)
 	a.NoError(e)
 
 	a.True(filler.IsTrain)
@@ -396,7 +396,7 @@ LABEL e INTO model_table;
 
 	// test with trainAndValDataset
 	ds := &trainAndValDataset{training: "TrainTable", validation: "EvalTable"}
-	filler, e = newXGBoostFiller(pr, ds, testDB)
+	filler, e = newAntXGBoostFiller(pr, ds, testDB)
 	a.NoError(e)
 	trainSlct := strings.TrimSuffix(strings.Replace(filler.StandardSelect, "\n", " ", -1), ";")
 	a.EqualValues("SELECT * FROM TrainTable", trainSlct)
@@ -413,7 +413,7 @@ LABEL e INTO model_table;
 
 	pr, e = parser.Parse(testPredictSelectIris)
 	a.NoError(e)
-	filler, e = newXGBoostFiller(pr, nil, testDB)
+	filler, e = newAntXGBoostFiller(pr, nil, testDB)
 	a.NoError(e)
 	a.Equal("class", filler.ResultColumn)
 	a.Equal("iris.predict", filler.OutputTable)
diff --git a/sql/executor.go b/sql/executor.go
index 3a098aa2f3..17187c56dd 100644
--- a/sql/executor.go
+++ b/sql/executor.go
@@ -373,7 +373,7 @@ func buildFiller(es *extendedSelect, ds *trainAndValDataset, fts fieldTypes, db
 		dataset = ds
 	}
 	if strings.HasPrefix(strings.ToUpper(es.estimator), `XGBOOST.`) {
-		return newXGBoostFiller(es, dataset, db)
+		return newAntXGBoostFiller(es, dataset, db)
 	}
 	return newFiller(es, dataset, fts, db)
 }
@@ -386,7 +386,7 @@ func train(wr *PipeWriter, tr *extendedSelect, db *DB, cwd string, modelDir stri
 
 	var program bytes.Buffer
 	if strings.HasPrefix(strings.ToUpper(tr.estimator), `XGBOOST.`) {
-		// TODO(sperlingxx): write a separate train pipeline for xgboost to support remote mode
+		// TODO(sperlingxx): write a separate train pipeline for ant-xgboost to support remote mode
 		if e := genXG(&program, tr, ds, fts, db); e != nil {
 			return fmt.Errorf("genXG %v", e)
 		}
@@ -452,7 +452,7 @@ func pred(wr *PipeWriter, pr *extendedSelect, db *DB, cwd string, modelDir strin
 
 	var buf bytes.Buffer
 	if strings.HasPrefix(strings.ToUpper(pr.estimator), `XGBOOST.`) {
-		// TODO(sperlingxx): write a separate pred pipeline for xgboost to support remote mode
+		// TODO(sperlingxx): write a separate pred pipeline for ant-xgboost to support remote mode
 		if e := genXG(&buf, pr, nil, fts, db); e != nil {
 			return fmt.Errorf("genXG %v", e)
 		}
diff --git a/sql/executor_test.go b/sql/executor_test.go
index 82f633ec4a..bf65b9d548 100644
--- a/sql/executor_test.go
+++ b/sql/executor_test.go
@@ -71,19 +71,19 @@ func TestSplitExtendedSQL(t *testing.T) {
 	a.Equal(`train a with b;`, s[0])
 }
 
-func TestExecutorTrainAnalyzePredictXGBoost(t *testing.T) {
+func TestExecutorTrainAnalyzePredictAntXGBoost(t *testing.T) {
 	a := assert.New(t)
 	modelDir, e := ioutil.TempDir("/tmp", "sqlflow_models")
 	a.Nil(e)
 	defer os.RemoveAll(modelDir)
 	a.NotPanics(func() {
-		stream := runExtendedSQL(testXGTrainSelectIris, testDB, modelDir, nil)
+		stream := runExtendedSQL(testAntXGTrainSelectIris, testDB, modelDir, nil)
 		a.True(goodStream(stream.ReadAll()))
 
-		stream = runExtendedSQL(testXGAnalyzeSelectIris, testDB, modelDir, nil)
+		stream = runExtendedSQL(testAntXGAnalyzeSelectIris, testDB, modelDir, nil)
 		a.True(goodStream(stream.ReadAll()))
 
-		stream = runExtendedSQL(testXGPredSelectIris, testDB, modelDir, nil)
+		stream = runExtendedSQL(testAntXGPredSelectIris, testDB, modelDir, nil)
 		a.True(goodStream(stream.ReadAll()))
 	})
 }
diff --git a/sql/python/sqlflow_submitter/xgboost/__init__.py b/sql/python/sqlflow_submitter/ant_xgboost/__init__.py
similarity index 86%
rename from sql/python/sqlflow_submitter/xgboost/__init__.py
rename to sql/python/sqlflow_submitter/ant_xgboost/__init__.py
index 47dd54a5e7..0123cb5d67 100644
--- a/sql/python/sqlflow_submitter/xgboost/__init__.py
+++ b/sql/python/sqlflow_submitter/ant_xgboost/__init__.py
@@ -12,7 +12,7 @@
 # limitations under the License.
 
 from .sqlflow_data_source import SQLFlowDataSource, SQLFlowDSConfig
-from .sqlflow_xgboost_main import run_with_sqlflow
-from .common import XGBoostError
+from .sqlflow_ant_xgboost_main import run_with_sqlflow
+from .common import AntXGBoostError
 
-__all__ = ['run_with_sqlflow', 'SQLFlowDataSource', 'SQLFlowDSConfig', 'XGBoostError']
+__all__ = ['run_with_sqlflow', 'SQLFlowDataSource', 'SQLFlowDSConfig', 'AntXGBoostError']
diff --git a/sql/python/sqlflow_submitter/xgboost/common.py b/sql/python/sqlflow_submitter/ant_xgboost/common.py
similarity index 94%
rename from sql/python/sqlflow_submitter/xgboost/common.py
rename to sql/python/sqlflow_submitter/ant_xgboost/common.py
index 098f183836..1d189a4520 100644
--- a/sql/python/sqlflow_submitter/xgboost/common.py
+++ b/sql/python/sqlflow_submitter/ant_xgboost/common.py
@@ -12,5 +12,5 @@
 # limitations under the License.
 
 
-class XGBoostError(Exception):
+class AntXGBoostError(Exception):
     pass
diff --git a/sql/python/sqlflow_submitter/xgboost/sqlflow_xgboost_main.py b/sql/python/sqlflow_submitter/ant_xgboost/sqlflow_ant_xgboost_main.py
similarity index 88%
rename from sql/python/sqlflow_submitter/xgboost/sqlflow_xgboost_main.py
rename to sql/python/sqlflow_submitter/ant_xgboost/sqlflow_ant_xgboost_main.py
index e6a0c8bf38..e50f9f8f15 100644
--- a/sql/python/sqlflow_submitter/xgboost/sqlflow_xgboost_main.py
+++ b/sql/python/sqlflow_submitter/ant_xgboost/sqlflow_ant_xgboost_main.py
@@ -16,8 +16,8 @@
 
 from launcher import register_data_source, config_helper, config_fields as cf, train, predict
 
-from sqlflow_submitter.xgboost.common import XGBoostError
-from sqlflow_submitter.xgboost.sqlflow_data_source import SQLFlowDSConfig, SQLFlowDataSource
+from sqlflow_submitter.ant_xgboost.common import AntXGBoostError
+from sqlflow_submitter.ant_xgboost.sqlflow_data_source import SQLFlowDSConfig, SQLFlowDataSource
 
 register_data_source('sqlflow', SQLFlowDSConfig, SQLFlowDataSource)
 
@@ -29,7 +29,7 @@ def run_with_sqlflow(mode: str,
                      column_config: str,
                      valid_data_source_config: str = None):
     if mode not in (cf.JobType.TRAIN, cf.JobType.PREDICT):
-        raise XGBoostError('Unknown run mode(%s) of xgboost launcher.' % mode)
+        raise AntXGBoostError('Unknown run mode(%s) of ant-xgboost launcher.' % mode)
     is_train = mode == cf.JobType.TRAIN
 
     def parse_json_str(string: str):
@@ -71,10 +71,10 @@ def parse_json_str(string: str):
             train_fields = cf.TrainFields(learning_fields, data_fields, model_fields)
             train(train_fields)
         except Exception as e:
-            raise XGBoostError('XGBoost training task failed: %s' % e)
+            raise AntXGBoostError('XGBoost training task failed: %s' % e)
     else:
         try:
             pred_fields = cf.PredictFields(data_fields, model_fields)
             predict(pred_fields)
         except Exception as e:
-            raise XGBoostError('XGBoost prediction task failed: %s' % e)
+            raise AntXGBoostError('XGBoost prediction task failed: %s' % e)
diff --git a/sql/python/sqlflow_submitter/xgboost/sqlflow_data_source.py b/sql/python/sqlflow_submitter/ant_xgboost/sqlflow_data_source.py
similarity index 95%
rename from sql/python/sqlflow_submitter/xgboost/sqlflow_data_source.py
rename to sql/python/sqlflow_submitter/ant_xgboost/sqlflow_data_source.py
index 145681caaf..c997572704 100644
--- a/sql/python/sqlflow_submitter/xgboost/sqlflow_data_source.py
+++ b/sql/python/sqlflow_submitter/ant_xgboost/sqlflow_data_source.py
@@ -19,7 +19,7 @@
 from launcher import DataSource, config_fields, XGBoostResult, XGBoostRecord
 from launcher.data_units import RecordBuilder
 
-from .common import XGBoostError
+from .common import AntXGBoostError
 from ..db import connect, db_generator, buffered_db_writer
 
 
@@ -40,7 +40,7 @@ def convert_shape(cls, value) -> typing.List:
         elif isinstance(value, typing.List):
             return value
         else:
-            raise XGBoostError('invalid shape %s of FeatureMeta' % value)
+            raise AntXGBoostError('invalid shape %s of FeatureMeta' % value)
 
 
 class SQLFlowDSConfig(typing.NamedTuple):
@@ -63,11 +63,11 @@ def __init__(self, rank: int, num_worker: int,
                  source_conf):
         super().__init__(rank, num_worker, column_conf, source_conf)
         if not isinstance(source_conf, SQLFlowDSConfig):
-            raise XGBoostError("SQLFlowDataSource: invalid source conf")
+            raise AntXGBoostError("SQLFlowDataSource: invalid source conf")
 
         # TODO: support tf.feature_column transformation
         if source_conf.is_tf_integrated:
-            raise XGBoostError('So far, tf transformation is not supported in xgboost job.')
+            raise AntXGBoostError('So far, tf transformation is not supported in ant-xgboost job.')
 
         self._train = source_conf.is_train
         self._rcd_builder = RecordBuilder(column_conf.features)
@@ -144,7 +144,7 @@ def writer_maker(table_schema):
 
         if not self._train:
             if not source_conf.output_table:
-                raise XGBoostError('Output_table must be defined in xgboost prediction job.')
+                raise AntXGBoostError('Output_table must be defined in xgboost prediction job.')
 
     def _read_impl(self):
         label = None
diff --git a/sql/python/sqlflow_submitter/xgboost/sqlflow_data_source_test.py b/sql/python/sqlflow_submitter/ant_xgboost/sqlflow_data_source_test.py
similarity index 98%
rename from sql/python/sqlflow_submitter/xgboost/sqlflow_data_source_test.py
rename to sql/python/sqlflow_submitter/ant_xgboost/sqlflow_data_source_test.py
index 3af49296a2..fb6214c701 100644
--- a/sql/python/sqlflow_submitter/xgboost/sqlflow_data_source_test.py
+++ b/sql/python/sqlflow_submitter/ant_xgboost/sqlflow_data_source_test.py
@@ -15,7 +15,7 @@
 import os
 from unittest import TestCase
 
-from sqlflow_submitter.xgboost.sqlflow_data_source import SQLFlowDSConfig, SQLFlowDataSource
+from sqlflow_submitter.ant_xgboost.sqlflow_data_source import SQLFlowDSConfig, SQLFlowDataSource
 from launcher import config_helper, config_fields, register_data_source, XGBoostRecord, XGBoostResult
 from launcher.data_source import create_data_source_init_fn
 from sqlflow_submitter.db_test import execute as db_exec
diff --git a/sql/python/test_magic_xgboost.py b/sql/python/test_magic_ant_xgboost.py
similarity index 98%
rename from sql/python/test_magic_xgboost.py
rename to sql/python/test_magic_ant_xgboost.py
index b03a0def98..220a9726e0 100644
--- a/sql/python/test_magic_xgboost.py
+++ b/sql/python/test_magic_ant_xgboost.py
@@ -46,7 +46,7 @@ class TestSQLFlowMagic(unittest.TestCase):
 USING sqlflow_models.my_xgboost_model;
 """
 
-    def test_xgboost(self):
+    def test_antxgboost(self):
         ipython.run_cell_magic("sqlflow", "", self.train_statement)
         ipython.run_cell_magic("sqlflow", "", self.pred_statement)