BohuTANG commented 11 months ago

Features and Capabilities

Databend is an open-source alternative to Snowflake, so we need a page to introduce the differences between Databend and Snowflake. Feel free to contribute if you notice any omissions.

	Category	Snowflake	Databend
Numeric Data Types	Data Types	Yes	Yes [1, 2]
String & Binary Data Types	Data Types	Yes	Yes
Logical Data Types	Data Types	Yes	Yes
Date & Time Data Types	Data Types	Yes	Yes
Geospatial Data Types	Data Types	Yes	Yes
Bitmap Data Types	Data Types	No	Yes
Semi-structured Data Types	Data Types	Yes	Yes
Database	Databases	Yes	Yes
Sequence	Sequences	Yes	Yes
Table	Tables	Yes	Yes
External Table(Table location in your bucket)	Tables	No	Yes
Vacuum	Tables	No	Yes
Clustering	Tables	Yes	Yes(Distributed)
Full-Text Index	Tables	No	Yes
Hive	Lake	Yes	Yes
Iceberg	Lake	Yes(Private Preview)	Yes
View	Views	Yes	Yes
Materialized Views	Views	Yes	Yes
User, Role, & Privilege	Privileges	Yes	Yes
Query	Queries	Yes	Yes
Update	General DML	Yes	Yes(Distributed)
Replace	General DML	No	Yes(Distributed)
Delete	General DML	Yes	Yes(Distributed)
Merge	General DML	Yes	Yes
Stage(Internal/External/Remove/List)	Data Loading	Yes	Yes
Query Stage File	Data Loading	Yes	Yes
Copy Into Table/Location	Data Loading	Yes	Yes(Distributed)
Transforming Data During a Load	Data Loading	Yes	Yes
Pipe	Data Loading	Yes	Yes(Cloud)
Task	Data Loading	Yes, minimum schedule is 1 minute	Yes, minimum schedule is 500 millisecond
Stream	Data Loading	Yes	Yes
Table Stream(Append-only/Standard)	Data Loading	Yes	Yes
User-Defined Functions	Functions	Yes	Yes
External Functions	Functions	Yes	Yes
Stored Procedure	Functions	Yes	Planning
AI Functions	Functions	Yes, 2024 Add	Yes
Window Function	Functions	Yes	Yes
Time Travel	Data Recovery	Yes	Yes
Data Sharing	Data Sharing	Yes	Yes
RBAC	Security	Yes	Yes
Network Policies	Security	Yes	Yes
Masking Policies	Security	Yes	Yes
Kafka Connect	Connectors	Yes	Yes
Flink CDC	Connectors	No	Yes
dbt	Connectors	Yes	Yes
Drivers	Drivers	Go Java Ptyhon Node.js	Go Java Python Node.js Rust
Embedded Python Library		No	Yes
Storage Format	Storage	MicroPartition	Parquet
Aggregate&Join&Sort Spill	Performance Optimization	Yes	Yes
Local Disk Cache	Performance Optimization	Yes	Yes
Profiling	Performance Optimization	Powerful	Powerful
CLI Client	Client	SnowSQL	BendSQL
TPC-H	Benchmark	Yes	Yes
TPC-DS	Benchmark	Yes	Yes
Supported Cloud Platforms	Cloud	AWS/GCP/AZURE	Any Cloud

Databend and Snowflake Functions Comparison

Mathematical Functions

Databend Function	Snowflake Function
`ABS(x)`	`ABS(x)`
`ACOS(x)`	`ACOS(x)`
`ASIN(x)`	`ASIN(x)`
`ATAN(x)`	`ATAN(x)`
`ATAN2(y, x)`	`ATAN2(y, x)`
`CEIL(x)`	`CEIL(x)`
`CEILING(x)`	`CEILING(x)`
`COS(x)`	`COS(x)`
`DEGREES(x)`	`DEGREES(x)`
`EXP(x)`	`EXP(x)`
`FLOOR(x)`	`FLOOR(x)`
`LN(x)`	`LN(x)`
`LOG(x)`	`LOG(x)`
`LOG10(x)`	`LOG10(x)`
`LOG2(x)`	`LOG2(x)`
`PI()`	`PI()`
`POW(x, y)`	`POW(x, y)`
`POWER(x, y)`	`POWER(x, y)`
`RADIANS(x)`	`RADIANS(x)`
`RAND()`	`RAND()`
`ROUND(x, d)`	`ROUND(x, d)`
`SIGN(x)`	`SIGN(x)`
`SIN(x)`	`SIN(x)`
`SQRT(x)`	`SQRT(x)`
`TAN(x)`	`TAN(x)`

String Functions

Databend Function	Snowflake Function
`ASCII(expr)`	`ASCII(expr)`
`CHAR(n, ...)`	`CHAR(n, ...)`
`CONCAT(expr1, ...)`	`CONCAT(expr1, ...)`
`CONCAT_WS(separator, expr1, ...)`	`CONCAT_WS(separator, expr1, ...)`
`INSTR(str, substr)`	`INSTR(str, substr)`
`LENGTH(str)`	`LENGTH(str)`
`LCASE(str)`	`LOWER(str)`
`LEFT(str, len)`	`LEFT(str, len)`
`LOWER(str)`	`LOWER(str)`
`LTRIM(str)`	`LTRIM(str)`
`POSITION(substr IN str)`	`POSITION(substr IN str)`
`REPEAT(str, count)`	`REPEAT(str, count)`
`REPLACE(str, from_str, to_str)`	`REPLACE(str, from_str, to_str)`
`REVERSE(str)`	`REVERSE(str)`
`RIGHT(str, len)`	`RIGHT(str, len)`
`RTRIM(str)`	`RTRIM(str)`
`SPACE(n)`	`SPACE(n)`
`SUBSTR(str, pos)`	`SUBSTR(str, pos)`
`SUBSTR(str, pos, len)`	`SUBSTR(str, pos, len)`
`SUBSTRING(str, pos)`	`SUBSTRING(str, pos)`
`SUBSTRING(str, pos, len)`	`SUBSTRING(str, pos, len)`
`TRIM([{BOTH \| LEADING \| TRAILING} [remstr] FROM] str)`	`TRIM([{BOTH \| LEADING \| TRAILING} [remstr] FROM] str)`
`UCASE(str)`	`UPPER(str)`
`UPPER(str)`	`UPPER(str)`

Date and Time Functions

Databend Function	Snowflake Function
`ADD_DAYS(date, interval)`	`DATEADD(day, interval, date)`
`ADD_HOURS(date, interval)`	`DATEADD(hour, interval, date)`
`ADD_MINUTES(date, interval)`	`DATEADD(minute, interval, date)`
`ADD_MONTHS(date, interval)`	`DATEADD(month, interval, date)`
`ADD_SECONDS(date, interval)`	`DATEADD(second, interval, date)`
`ADD_YEARS(date, interval)`	`DATEADD(year, interval, date)`
`DATE(expr)`	`DATE(expr)`
`DAY(date)`	`DAY(date)`
`DAYNAME(date)`	`DAYNAME(date)`
`DAY_OF_MONTH(date)`	`DAYOFMONTH(date)`
`DAY_OF_WEEK(date)`	`DAYOFWEEK(date)`
`DAY_OF_YEAR(date)`	`DAYOFYEAR(date)`
`HOUR(date)`	`HOUR(date)`
`LAST_DAY(date)`	`LAST_DAY(date)`
`MINUTE(time)`	`MINUTE(time)`
`MONTH(date)`	`MONTH(date)`
`NOW()`	`CURRENT_TIMESTAMP()`
`SECOND(time)`	`SECOND(time)`
`TO_DATE(expr)`	`TO_DATE(expr)`
`TO_TIMESTAMP(expr)`	`TO_TIMESTAMP(expr)`
`WEEK(date)`	`WEEK(date)`
`YEAR(date)`	`YEAR(date)`
`YESTERDAY()`	`DATEADD(day, -1, CURRENT_DATE())`
`TOMORROW()`	`DATEADD(day, 1, CURRENT_DATE())`
`TO_START_OF_DAY(expr)`	`DATE_TRUNC('day', expr)`
`TO_START_OF_HOUR(expr)`	`DATE_TRUNC('hour', expr)`
`TO_START_OF_MINUTE(expr)`	`DATE_TRUNC('minute', expr)`
`TO_START_OF_MONTH(expr)`	`DATE_TRUNC('month', expr)`
`TO_START_OF_QUARTER(expr)`	`DATE_TRUNC('quarter', expr)`
`TO_START_OF_WEEK(expr)`	`DATE_TRUNC('week', expr)`
`TO_START_OF_YEAR(expr)`	`DATE_TRUNC('year', expr)`
`TO_UNIX_TIMESTAMP(expr)`	`TO_TIMESTAMP(expr)`
`TO_YEARMONTH(expr)`	`TO_CHAR(expr, 'YYYY-MM')`
`TO_YYYYMMDD(expr)`	`TO_CHAR(expr, 'YYYYMMDD')`
`TO_YYYYMMDDHH(expr)`	`TO_CHAR(expr, 'YYYYMMDDHH')`
`TO_YYYYMMDDHHMMSS(expr)`	`TO_CHAR(expr, 'YYYYMMDDHHMMSS')`

Aggregate Functions

Databend Function	Snowflake Function
`AVG(x)`	`AVG(x)`
`COUNT(x)`	`COUNT(x)`
`MAX(x)`	`MAX(x)`
`MIN(x)`	`MIN(x)`
`SUM(x)`	`SUM(x)`

Conversion Functions

Databend Function	Snowflake Function
`CAST(expr AS type)`	`CAST(expr AS type)`
`TO_BOOLEAN(expr)`	`CAST(expr AS BOOLEAN)`
`TO_STRING(expr)`	`CAST(expr AS STRING)`
`TO_INT32(expr)`	`CAST(expr AS INT)`
`TO_INT64(expr)`	`CAST(expr AS BIGINT)`
`TO_UINT32(expr)`	`CAST(expr AS NUMBER)`
`TO_UINT64(expr)`	`CAST(expr AS NUMBER)`
`TO_FLOAT32(expr)`	`CAST(expr AS FLOAT)`
`TO_FLOAT64(expr)`	`CAST(expr AS DOUBLE)`
`TO_DATE(expr)`	`CAST(expr AS DATE)`
`TO_TIMESTAMP(expr)`	`CAST(expr AS TIMESTAMP)`
`TRY_CAST(expr AS type)`	`TRY_CAST(expr AS type)`

JSON Functions

Databend Function	Snowflake Function
`JSON_OBJECT(key1, value1[, key2, value2[, ...]])`	`OBJECT_CONSTRUCT(key1, value1[, key2, value2[, ...]])`
`PARSE_JSON(expr)`	`PARSE_JSON(expr)`
`JSON_EXTRACT_PATH_TEXT(expr, path_name)`	`GET(expr, path_name)`
`JSON_PRETTY(json_string)`	`TO_JSON_STRING(json_string)`
`JSON_ARRAY(value1[, value2[, ...]])`	`ARRAY_CONSTRUCT(value1[, value2[, ...]])`
`JSON_PATH_QUERY(variant, path_name)`	`PATH(expr, path_name)`
`JSON_PATH_QUERY_FIRST(variant, path_name)`	`PATH(expr, path_name)`
`CHECK_JSON(expr)`	`IS_JSON(expr)`
`GET_PATH(variant, path_name)`	`GET_PATH(variant, path_name)`
`JSON_PATH_EXISTS(json_data, json_path_expression)`	`JSON_PATH_EXISTS(json_data, json_path_expression)`
`JSON_OBJECT_KEEP_NULL(key1, value1[, key2, value2[, ...]])`	`OBJECT_CONSTRUCT_KEEP_NULL(key1, value1[, key2, value2[, ...]])`
`IS_INTEGER(expr)`	`IS_INTEGER(expr)`
`IS_NULL_VALUE(expr)`	`IS_NULL_VALUE(expr)`
`IS_STRING(expr)`	`IS_STRING(expr)`
`IS_BOOLEAN(expr)`	`IS_BOOLEAN(expr)`
`FLATTEN(INPUT => expr [, PATH => expr ] [ , OUTER => TRUE \| FALSE ] [ , RECURSIVE => TRUE \| FALSE ] [ , MODE => 'OBJECT' \| 'ARRAY' \| 'BOTH' ])`	`FLATTEN(INPUT => expr [, PATH => expr ] [ , OUTER => TRUE \| FALSE ] [ , RECURSIVE => TRUE \| FALSE ] [ , MODE => 'OBJECT' \| 'ARRAY' \| 'BOTH' ])`
`IS_ARRAY(expr)`	`IS_ARRAY(expr)`
`GET(variant, index)`	`GET(variant, index)`
`JSON_PATH_QUERY_ARRAY(variant, path_name)`	`PATH_ARRAY(variant, path_name)`
`GET_IGNORE_CASE(variant, field_name)`	`GET_IGNORE_CASE(variant, field_name)`
`JSON_ARRAY_ELEMENTS(json_string)`	`ARRAY_ELEMENTS(json_string)`
`JSON_STRIP_NULLS(json_string)`	`REMOVE_NULLS(json_string)`
`AS_BOOLEAN(variant)`	`CAST(variant AS BOOLEAN)`
`AS_INTEGER(variant)`	`CAST(variant AS INTEGER)`
`AS_FLOAT(variant)`	`CAST(variant AS FLOAT)`
`AS_STRING(variant)`	`CAST(variant AS STRING)`
`AS_ARRAY(variant)`	`CAST(variant AS ARRAY)`
`AS_OBJECT(variant)`	`CAST(variant AS OBJECT)`

Bitmap Functions

Databend Function	Snowflake Function
`BUILD_BITMAP(expr)`	N/A
`TO_BITMAP(expr)`	N/A
`BITMAP_AND(expr1, expr2)`	N/A
`BITMAP_OR(expr1, expr2)`	N/A
`BITMAP_XOR(expr1, expr2)`	N/A
`BITMAP_HAS_ALL(expr1, expr2)`	N/A
`BITMAP_HAS_ANY(expr1, expr2)`	N/A
`BITMAP_TO_STRING(expr)`	N/A

Conditional Functions

Databend Function	Snowflake Function
`IF(cond, expr1, expr2)`	`IFF(cond, expr1, expr2)`
`NULLIF(expr1, expr2)`	`NULLIF(expr1, expr2)`
`IFNULL(expr1, expr2)`	`IFNULL(expr1, expr2)`
`COALESCE(expr1, expr2[, ...])`	`COALESCE(expr1, expr2[, ...])`

Encryption and Hash Functions

Databend Function	Snowflake Function
`MD5(expr)`	`MD5(expr)`
`SHA(expr)`	`SHA(expr)`
`SHA2(expr, x)`	`SHA2(expr, x)`
`CRC32(expr)`	`CRC32(expr)`
`XXHASH32(expr)`	N/A
`XXHASH64(expr)`	N/A
`BLAKE3(expr)`	N/A
`SIPHASH64(expr)`	N/A
`CITY64WITHSEED(expr1, expr2)`	N/A

Window Functions

Databend Function	Snowflake Function
`ROW_NUMBER()`	`ROW_NUMBER()`
`RANK()`	`RANK()`
`DENSE_RANK()`	`DENSE_RANK()`
`PERCENT_RANK()`	`PERCENT_RANK()`
`CUME_DIST()`	`CUME_DIST()`
`NTILE(n)`	`NTILE(n)`
`LAG(expr, n, default)`	`LAG(expr, n, default)`
`LEAD(expr, n, default)`	`LEAD(expr, n, default)`
`FIRST_VALUE(expr)`	`FIRST_VALUE(expr)`
`LAST_VALUE(expr)`	`LAST_VALUE(expr)`
`NTH_VALUE(expr, n)`	`NTH_VALUE(expr, n)`

Array Functions

Databend Function	Snowflake Function
`ARRAY_REDUCE(array, lambda)`	N/A
`ARRAY_FLATTEN(array)`	N/A
`SLICE(array, start[, end])`	`SLICE(array, start[, end])`
`ARRAY_TO_STRING(array, '<separator>')`	`ARRAY_TO_STRING(array, '<separator>')`
`CONTAINS(array, element)`	`ARRAY_CONTAINS(array, element)`
`ARRAY_FILTER(array, lambda)`	N/A
`ARRAY_SORT(array[, order[, nullposition]])`	`ARRAY_SORT(array[, order[, nullposition]])`
`UNNEST(array)`	`UNNEST(array)`
`ARRAY_CONCAT(array1, array2)`	`ARRAY_CAT(array1, array2)`
`GET(array, index)`	`GET(array, index)`
`ARRAY_INDEX_OF(array, element)`	`ARRAY_INDEX_OF(array, element)`
`ARRAY_UNIQUE(array)`	`ARRAY_UNIQUE(array)`
`ARRAY_REMOVE_FIRST(array)`	N/A
`ARRAY_TRANSFORM(array, lambda)`	N/A
`ARRAY_DISTINCT(array)`	`ARRAY_DISTINCT(array)`
`ARRAY_APPEND(array, element)`	`ARRAY_APPEND(array, element)`
`ARRAY_PREPEND(element, array)`	`ARRAY_PREPEND(element, array)`
`ARRAY_LENGTH(array)`	`ARRAY_LENGTH(array)`
`ARRAY_APPLY(array, lambda)`	N/A

Geospatial Functions

Databend Function	Snowflake Function
`H3_EXACT_EDGE_LENGTH_KM(h3)`	`H3_EXACT_EDGE_LENGTH_KM(h3)`
`H3_EDGE_LENGTH_M(1)`	`H3_EDGE_LENGTH_M(1)`
`H3_LINE(h3, a_h3)`	`H3_LINE(h3, a_h3)`
`H3_EDGE_LENGTH_KM(res)`	`H3_EDGE_LENGTH_KM(res)`
`H3_EXACT_EDGE_LENGTH_M(h3)`	`H3_EXACT_EDGE_LENGTH_M(h3)`
`GEOHASH_DECODE('<geohashed-string>')`	`GEOHASH_DECODE('<geohashed-string>')`
`H3_HEX_AREA_M2(res)`	`H3_HEX_AREA_M2(res)`
`H3_TO_GEO_BOUNDARY(h3)`	`H3_TO_GEO_BOUNDARY(h3)`
`H3_GET_UNIDIRECTIONAL_EDGES_FROM_HEXAGON(h3)`	`H3_GET_UNIDIRECTIONAL_EDGES_FROM_HEXAGON(h3)`
`H3_HEX_AREA_KM2(res)`	`H3_HEX_AREA_KM2(res)`
`H3_IS_VALID(h3)`	`H3_IS_VALID(h3)`
`H3_TO_GEO(h3)`	`H3_TO_GEO(h3)`
`H3_UNIDIRECTIONAL_EDGE_IS_VALID(h3)`	`H3_UNIDIRECTIONAL_EDGE_IS_VALID(h3)`
`GEO_TO_H3(lon, lat, res)`	`GEO_TO_H3(lon, lat, res)`
`GEOHASH_ENCODE(lon, lat)`	`GEOHASH_ENCODE(lon, lat)`
`POINT_IN_POLYGON((x,y), [(a,b), (c,d), (e,f) ... ])`	`POINT_IN_POLYGON((x,y), [(a,b), (c,d), (e,f) ... ])`
`H3_DISTANCE(h3, a_h3)`	`H3_DISTANCE(h3, a_h3)`
`H3_CELL_AREA_RADS2(h3)`	`H3_CELL_AREA_RADS2(h3)`
`H3_TO_CENTER_CHILD(h3, res)`	`H3_TO_CENTER_CHILD(h3, res)`
`H3_CELL_AREA_M2(h3)`	`H3_CELL_AREA_M2(h3)`
`H3_GET_FACES(h3)`	`H3_GET_FACES(h3)`
`H3_IS_PENTAGON(h3)`	`H3_IS_PENTAGON(h3)`
`STRING_TO_H3(h3)`	`STRING_TO_H3(h3)`
`H3_GET_UNIDIRECTIONAL_EDGE(h3, a_h3)`	`H3_GET_UNIDIRECTIONAL_EDGE(h3, a_h3)`
`H3_GET_BASE_CELL(h3)`	`H3_GET_BASE_CELL(h3)`
`H3_GET_UNIDIRECTIONAL_EDGE_BOUNDARY(h3)`	`H3_GET_UNIDIRECTIONAL_EDGE_BOUNDARY(h3)`
`H3_GET_DESTINATION_INDEX_FROM_UNIDIRECTIONAL_EDGE(h3)`	`H3_GET_DESTINATION_INDEX_FROM_UNIDIRECTIONAL_EDGE(h3)`
`H3_TO_PARENT(h3, parent_res)`	`H3_TO_PARENT(h3, parent_res)`
`H3_NUM_HEXAGONS(res)`	`H3_NUM_HEXAGONS(res)`
`H3_TO_CHILDREN(h3, child_res)`	`H3_TO_CHILDREN(h3, child_res)`
`H3_GET_INDEXES_FROM_UNIDIRECTIONAL_EDGE(h3)`	`H3_GET_INDEXES_FROM_UNIDIRECTIONAL_EDGE(h3)`
`H3_TO_STRING(h3)`	`H3_TO_STRING(h3)`
`H3_K_RING(h3, k)`	`H3_K_RING(h3, k)`
`H3_IS_RES_CLASS_III(h3)`	`H3_IS_RES_CLASS_III(h3)`
`H3_INDEXES_ARE_NEIGHBORS(h3, a_h3)`	`H3_INDEXES_ARE_NEIGHBORS(h3, a_h3)`
`H3_GET_ORIGIN_INDEX_FROM_UNIDIRECTIONAL_EDGE(h3)`	`H3_GET_ORIGIN_INDEX_FROM_UNIDIRECTIONAL_EDGE(h3)`
`H3_GET_RESOLUTION(h3)`	`H3_GET_RESOLUTION(h3)`

Other Functions

Databend Function	Snowflake Function
`NEXTVAL(seq_name)`	`NEXTVAL(seq_name)`
`QUOTE(str)`	`QUOTE(str)`

ZhiHanZ commented 11 months ago

Feature	Snowflake	Databend
Kafka Connect	Yes	Yes
Flink CDC	No	Yes
dbt	Yes	Yes
go driver	Yes	Yes
java driver	Yes	Yes
rust driver	No	Yes
python driver	Yes	Yes
nodejs driver	Yes	Planning
embedded python lib	No	Yes
Iceberg	Private Preview	Yes

PsiACE commented 11 months ago

we hava a nodejs driver, see:

In addition, although we do not yet support geospatial types, we have already implemented a wide range of geospatial functions. I believe this is worth mentioning.

https://databend.rs/doc/sql-functions/geo-functions/

I think, in Storage Format, perhaps we can also add our native format and indicate that it can bring better performance.

xudong963 commented 11 months ago

We also support aggregate and hash join spilling.

Chasen-Zhang commented 9 months ago

Summary

Databend is an open-source alternative to Snowflake, so we need a page to introduce the differences between Databend and Snowflake. Feel free to contribute if you notice any omissions.

Category Snowflake Databend Numeric Data Types Data Types Yes Yes [1, 2] String & Binary Data Types Data Types Yes Yes Logical Data Types Data Types Yes Yes Date & Time Data Types Data Types Yes Yes Geospatial Data Types Data Types Yes No(Geo functions) Bitmap Data Types Data Types No Yes Semi-structured Data Types Data Types Yes Yes Database Databases Yes Yes Table Tables Yes Yes External Table Tables Yes Yes Vacuum Tables No Yes Clustering Tables Yes Yes(Distributed) Hive Lake Yes Yes Iceberg Lake Yes(Private Preview) Yes View Views Yes Yes Materialized Views Views Yes Yes(Need Doc) User, Role, & Privilege Privileges Yes Yes Query Queries Yes Yes Update General DML Yes Yes(Distributed) Replace General DML No Yes(Distributed) Delete General DML Yes Yes(Distributed) Merge General DML Yes Yes Stage(Internal/External/Remove/List) Data Loading Yes Yes Query Stage File Data Loading Yes Yes Copy Into Table/Location Data Loading Yes Yes(Distributed) Transforming Data During a Load Data Loading Yes Yes Table Pipe Data Loading Yes Yes(Cloud) Table Task Data Loading Yes Yes Table Stream Data Loading Yes Yes User-Defined Functions Functions Yes Yes External Functions Functions Yes Yes Stored Procedure Functions Yes No AI Functions Functions No Yes Window Function Functions Yes Yes Time Travel Data Recovery Yes Yes Data Sharing Data Sharing Yes Yes RBAC Security Yes Yes Network Policies Security Yes Yes Masking Policies Security Yes Yes Kafka Connect Connectors Yes Yes Flink CDC Connectors No Yes dbt Connectors Yes Yes Drivers Drivers Go Java Ptyhon Node.js Go Java Python Node.js Rust Embedded Python Library No Yes Storage Format Storage MicroPartition Parquet Aggregate&Join Spill Performance Optimization Yes Yes Local Disk Cache Performance Optimization Yes Yes Profiling Performance Optimization Powerful Medium CLI Client Client SnowSQL BendSQL TPC-H Benchmark Yes Yes TPC-DS Benchmark Yes Yes Supported Cloud Platforms Cloud AWS/GCP/AZURE Any Cloud

@BohuTANG Could you help me change the address of the connection， Here are the rules： /doc/sql-reference/ => /sql/sql-reference/ /doc/sql-commands/ => /sql/sql-commands/ /doc/sql-functions/ =>/sql/sql-functions/ (👆 Although I redirected all of these, it's better to change them all together. And you can directly change the domain name to https://docs.databend.com )

https://docs.databend.com/load-data/pipeline => https://docs.databend.com/doc/load-data/pipeline https://databend.rs/blog/2023-08-01-iceberg-integration=> https://www.databend.com/blog/2023-08-01-iceberg-integration/

Thank you in advance！

cdmikechen commented 8 months ago

@BohuTANG Wish to support Geospatial Data Types, we used to have a lot of spatial data needs, and if databend can support geo, it will be a great help to us ~

datafuselabs / databend

Databend vs. Snowflake Features and Capabilities #13059