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DBMS > Geode vs. Hazelcast vs. Ignite vs. Sphinx

System Properties Comparison Geode vs. Hazelcast vs. Ignite vs. Sphinx

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonHazelcast  Xexclude from comparisonIgnite  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA widely adopted in-memory data gridApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeKey-value storeKey-value store
Relational DBMS
Search engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.92
Rank#131  Overall
#23  Key-value stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitegeode.apache.orghazelcast.comignite.apache.orgsphinxsearch.com
Technical documentationgeode.apache.org/­docshazelcast.org/­imdg/­docsapacheignite.readme.io/­docssphinxsearch.com/­docs
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.HazelcastApache Software FoundationSphinx Technologies Inc.
Initial release2002200820152001
Current release1.1, February 20175.3.6, November 2023Apache Ignite 2.63.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++, Java, .NetC++
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredAll OS with a Java VMLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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.noyes infothe object must implement a serialization strategyyes
Secondary indexesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (OQL)SQL-like query languageANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor Servicesyes (compute grid and cache interceptors can be used instead)no
Triggersyes infoCache Event Listenersyes infoEventsyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoReplicated Mapyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodeone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights per client and object definableRole-based access controlSecurity Hooks for custom implementationsno

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