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DBMS > Apache Phoenix vs. CrateDB vs. Oracle Coherence vs. Transwarp KunDB

System Properties Comparison Apache Phoenix vs. CrateDB vs. Oracle Coherence vs. Transwarp KunDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCrateDB  Xexclude from comparisonOracle Coherence  Xexclude from comparisonTranswarp KunDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed Database based on LuceneOracles in-memory data grid solutionOLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.92
Rank#130  Overall
#22  Key-value stores
Score0.10
Rank#344  Overall
#151  Relational DBMS
Websitephoenix.apache.orgcratedb.comwww.oracle.com/­java/­coherencewww.transwarp.cn/­en/­product/­kundb
Technical documentationphoenix.apache.orgcratedb.com/­docsdocs.oracle.com/­en/­middleware/­standalone/­coherence
DeveloperApache Software FoundationCrateOracleTranswarp
Initial release201420132007
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201914.1, August 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Sourcecommercialcommercial
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 languageJavaJavaJava
Server operating systemsLinux
Unix
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VM
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 SQLyesyes, but no triggers and constraints, and PostgreSQL compatibilitynoyes
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JCache
JPA
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.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
.Net
C++
Java
Server-side scripts infoStored proceduresuser defined functionsuser defined functions (Javascript)noyes
Triggersnonoyes infoLive Eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Configurable replication on table/partition-levelyes, with selectable consistency level
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
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 strategyconfigurableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infooptionallyyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyrights management via user accountsauthentification to access the cache via certificates or http basic authenticationyes
More information provided by the system vendor
Apache PhoenixCrateDBOracle CoherenceTranswarp KunDB
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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More resources
Apache PhoenixCrateDBOracle CoherenceTranswarp KunDB
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