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DBMS > Apache Phoenix vs. GridGain vs. InfluxDB vs. KeyDB

System Properties Comparison Apache Phoenix vs. GridGain vs. InfluxDB vs. KeyDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGridGain  Xexclude from comparisonInfluxDB  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGridGain is an in-memory computing platform, built on Apache IgniteDBMS for storing time series, events and metricsAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMSKey-value store
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score24.39
Rank#28  Overall
#1  Time Series DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Websitephoenix.apache.orgwww.gridgain.comwww.influxdata.com/­products/­influxdb-overviewgithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationphoenix.apache.orgwww.gridgain.com/­docs/­index.htmldocs.influxdata.com/­influxdbdocs.keydb.dev
DeveloperApache Software FoundationGridGain Systems, Inc.EQ Alpha Technology Ltd.
Initial release2014200720132019
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019GridGain 8.5.12.7.6, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoBSD-3
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.
Implementation languageJavaJava, C++, .NetGoC++
Server operating systemsLinux
Unix
Windows
Linux
OS X
Solaris
Windows
Linux
OS X infothrough Homebrew
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesNumeric data and Stringspartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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.noyesnono
Secondary indexesyesyesnoyes infoby using the Redis Search module
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLSQL-like query languageno
APIs and other access methodsJDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
JSON over UDP
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresuser defined functionsyes (compute grid and cache interceptors can be used instead)noLua
Triggersnoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoin enterprise version onlySharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes (replicated cache)selectable replication factor infoin enterprise version onlyMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoDepending on used storage engineyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancySecurity Hooks for custom implementationssimple rights management via user accountssimple password-based access control and ACL
More information provided by the system vendor
Apache PhoenixGridGainInfluxDBKeyDB
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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