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DBMS > Apache Phoenix vs. Couchbase vs. GridDB vs. Manticore Search vs. TimescaleDB

System Properties Comparison Apache Phoenix vs. Couchbase vs. GridDB vs. Manticore Search vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCouchbase infoOriginally called Membase  Xexclude from comparisonGridDB  Xexclude from comparisonManticore Search  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile databaseScalable in-memory time series database optimized for IoT and Big DataMulti-storage database for search, including full-text search.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSDocument storeTime Series DBMSSearch engineTime Series DBMS
Secondary database modelsKey-value store infooriginating from the former Membase product and supporting the Memcached protocol
Spatial DBMS infousing the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Relational DBMS
Time Series DBMS infousing the Manticore Columnar LibraryRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score17.30
Rank#36  Overall
#5  Document stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitephoenix.apache.orgwww.couchbase.comgriddb.netmanticoresearch.comwww.timescale.com
Technical documentationphoenix.apache.orgdocs.couchbase.comdocs.griddb.netmanual.manticoresearch.comdocs.timescale.com
DeveloperApache Software FoundationCouchbase, Inc.Toshiba CorporationManticore SoftwareTimescale
Initial release20142011201320172017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 20235.1, August 20226.0, February 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBusiness Source License (BSL 1.1); Commercial licenses also availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++, Go and ErlangC++C++C
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
LinuxFreeBSD
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesFixed schemayes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleannumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoCan index from XMLyes
Secondary indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesSQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use casesSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCCLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
Go
Java
JavaScript infoNode.js
Kotlin
PHP
Python
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsFunctions and timers in JavaScript and UDFs in Java, Python, SQL++nouser defined functionsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes infovia the TAP protocolyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic ShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication infoincluding cross data center replication
Source-replica replication
Source-replica replicationSynchronous replication based on Galera librarySource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency infoselectable on a per-operation basis
Immediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoEphemeral bucketsyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyUser and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.Access rights for users can be defined per databasenofine grained access rights according to SQL-standard
More information provided by the system vendor
Apache PhoenixCouchbase infoOriginally called MembaseGridDBManticore SearchTimescaleDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
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More resources
Apache PhoenixCouchbase infoOriginally called MembaseGridDBManticore SearchTimescaleDB
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Recent citations in the news

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TimescaleDB Is a Vector Database Now, Too
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Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

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29 January 2019, TechCrunch

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