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DBMS > AntDB vs. Databricks vs. Google BigQuery vs. Vitess

System Properties Comparison AntDB vs. Databricks vs. Google BigQuery vs. Vitess

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Editorial information provided by DB-Engines
NameAntDB  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionA scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with OracleThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Large scale data warehouse service with append-only tablesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#303  Overall
#137  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.asiainfo.com/­en_us/­product_aisware_antdb_detail.htmlwww.databricks.comcloud.google.com/­bigqueryvitess.io
Technical documentationdocs.databricks.comcloud.google.com/­bigquery/­docsvitess.io/­docs
Social network pagesLinkedInTwitterFacebook
DeveloperAsiaInfo Technologies LimitedDatabricksGoogleThe Linux Foundation, PlanetScale
Initial release201320102013
Current release15.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGo
Server operating systemshostedhostedDocker
Linux
macOS
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL2016 compliantwith Databricks SQLyesyes infowith proprietary extensions
APIs and other access methodsJDBC
MySQL protocol compliant
ODBC
JDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesPython
R
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functions infoin JavaScriptyes infoproprietary syntax
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno infoSince BigQuery is designed for querying dataACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Users with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
AntDBDatabricksGoogle BigQueryVitess
Specific characteristicsAntDB was initiated in 2008. On the core system of operators, AntDB provides online...
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Supported database models : In addition to the Document store and Relational DBMS...
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Competitive advantagesHTAP mixed load: AntDB is a universal, enterprise-level distributed relational database,...
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Typical application scenariosAs the core software of large enterprise, AntDB supports multi-scenario deployment....
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Key customersChina Mobile, China Telecom, China Unicom, Aeon Life, China Mobile Tietong, CITIC...
» more
Market metricsMore than 1 billion subscribers in 24 provinces across China are served by AntDB...
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Licensing and pricing modelsCertificates and licenses CMMI5 Certificate licensed by CMMI Institute IT Product...
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More resources
AntDBDatabricksGoogle BigQueryVitess
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