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DBMS > AntDB vs. CrateDB vs. HBase vs. ObjectBox

System Properties Comparison AntDB vs. CrateDB vs. HBase vs. ObjectBox

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Editorial information provided by DB-Engines
NameAntDB  Xexclude from comparisonCrateDB  Xexclude from comparisonHBase  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionA scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with OracleDistributed Database based on LuceneWide-column store based on Apache Hadoop and on concepts of BigTableExtremely fast embedded database for small devices, IoT and Mobile
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Wide column storeObject oriented DBMS
Secondary database modelsRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#317  Overall
#141  Relational DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Websitewww.asiainfo.com/­en_us/­product_aisware_antdb_detail.htmlcratedb.comhbase.apache.orgobjectbox.io
Technical documentationcratedb.com/­docshbase.apache.org/­book.htmldocs.objectbox.io
DeveloperAsiaInfo Technologies LimitedCrateApache Software Foundation infoApache top-level project, originally developed by PowersetObjectBox Limited
Initial release201320082017
Current release2.3.4, January 2021
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache version 2Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaC and C++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
Unix
Windows infousing Cygwin
Android
iOS
Linux
macOS
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL2016 compliantyes, but no triggers and constraints, and PostgreSQL compatibilitynono
APIs and other access methodsJDBC
MySQL protocol compliant
ODBC
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
Proprietary native API
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Server-side scripts infoStored proceduresuser defined functions (Javascript)yes infoCoprocessors in Javano
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication
Source-replica replication
online/offline synchronization between client and server
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategySingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyesno
User concepts infoAccess controlrights management via user accountsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes
More information provided by the system vendor
AntDBCrateDBHBaseObjectBox
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AntDBCrateDBHBaseObjectBox
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