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DBMS > Ignite vs. KeyDB vs. Sphinx vs. Splice Machine vs. Tkrzw

System Properties Comparison Ignite vs. KeyDB vs. Sphinx vs. Splice Machine vs. Tkrzw

Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonKeyDB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value store
Relational DBMS
Key-value storeSearch engineRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteignite.apache.orggithub.com/­Snapchat/­KeyDB
keydb.dev
sphinxsearch.comsplicemachine.comdbmx.net/­tkrzw
Technical documentationapacheignite.readme.io/­docsdocs.keydb.devsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperApache Software FoundationEQ Alpha Technology Ltd.Sphinx Technologies Inc.Splice MachineMikio Hirabayashi
Initial release20152019200120142020
Current releaseApache Ignite 2.63.5.1, February 20233.1, March 20210.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoBSD-3Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetC++C++JavaC++
Server operating systemsLinux
OS X
Solaris
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesnoyesno
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.yesnono
Secondary indexesyesyes infoby using the Redis Search moduleyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like query language (SphinxQL)yesno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol infoRESP - REdis Serialization ProtocoProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Luanoyes infoJavano
Triggersyes (cache interceptors and events)nonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Multi-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDOptimistic locking, atomic execution of commands blocks and scriptsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infousing specific database classes
User concepts infoAccess controlSecurity Hooks for custom implementationssimple password-based access control and ACLnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
IgniteKeyDBSphinxSplice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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