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DBMS > CrateDB vs. gStore vs. HBase vs. Realm

System Properties Comparison CrateDB vs. gStore vs. HBase vs. Realm

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisongStore  Xexclude from comparisonHBase  Xexclude from comparisonRealm  Xexclude from comparison
DescriptionDistributed Database based on LuceneA native Graph DBMS to store and maintain very large RDF datasets.Wide-column store based on Apache Hadoop and on concepts of BigTableA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Graph DBMS
RDF store
Wide column storeDocument store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.04
Rank#359  Overall
#37  Graph DBMS
#18  RDF stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score7.60
Rank#52  Overall
#9  Document stores
Websitecratedb.comen.gstore.cnhbase.apache.orgrealm.io
Technical documentationcratedb.com/­docsen.gstore.cn/­#/­enDocshbase.apache.org/­book.htmlrealm.io/­docs
DeveloperCrateApache Software Foundation infoApache top-level project, originally developed by PowersetRealm, acquired by MongoDB in May 2019
Initial release2013201620082014
Current release1.2, November 20232.3.4, January 2021
License infoCommercial or Open SourceOpen SourceOpen Source infoBSDOpen Source infoApache version 2Open Source
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 languageJavaC++Java
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxLinux
Unix
Windows infousing Cygwin
Android
Backend: server-less
iOS
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free and OWL/RDFS-schema supportschema-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.nononono
Secondary indexesyesnoyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynonono
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HTTP API
SPARQL 1.1
Java API
RESTful HTTP API
Thrift
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++
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresuser defined functions (Javascript)yesyes infoCoprocessors in Javano inforuns within the applications so server-side scripts are unnecessary
Triggersnoyesyes infoChange Listeners
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
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyyesSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonoyesyes infoIn-Memory realm
User concepts infoAccess controlrights management via user accountsUsers, roles and permissions, Role-Based Access Control (RBAC) supportedAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes
More information provided by the system vendor
CrateDBgStoreHBaseRealm
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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CrateDBgStoreHBaseRealm
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