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DBMS > CrateDB vs. EsgynDB vs. HBase vs. RocksDB

System Properties Comparison CrateDB vs. EsgynDB vs. HBase vs. RocksDB

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonHBase  Xexclude from comparisonRocksDB  Xexclude from comparison
DescriptionDistributed Database based on LuceneEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionWide-column store based on Apache Hadoop and on concepts of BigTableEmbeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSWide column storeKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.76
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#18  Time Series DBMS
#8  Vector DBMS
Score0.26
Rank#311  Overall
#141  Relational DBMS
Score31.60
Rank#26  Overall
#2  Wide column stores
Score4.52
Rank#80  Overall
#10  Key-value stores
Websitecratedb.comwww.esgyn.cnhbase.apache.orgrocksdb.org
Technical documentationcratedb.com/­docshbase.apache.org/­book.htmlgithub.com/­facebook/­rocksdb/­wiki
DeveloperCrateEsgynApache Software Foundation infoApache top-level project, originally developed by PowersetFacebook, Inc.
Initial release2013201520082013
Current release2.3.4, January 20218.10.0, December 2023
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoApache version 2Open Source infoBSD
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++, JavaJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxLinux
Unix
Windows infousing Cygwin
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROno
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 indexesyesyesnono
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesnono
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP API
Thrift
C++ API
Java 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
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Groovy
Java
PHP
Python
Scala
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)Java Stored Proceduresyes infoCoprocessors in Javano
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication between multi datacentersMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynoyesnono
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 strategyACIDSingle row ACID (across millions of columns)yes
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.nonoyesyes
User concepts infoAccess controlrights management via user accountsfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno
More information provided by the system vendor
CrateDBEsgynDBHBaseRocksDB
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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3rd partiesSpeedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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More resources
CrateDBEsgynDBHBaseRocksDB
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