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DBMS > Greenplum vs. Hazelcast vs. Sphinx

System Properties Comparison Greenplum vs. Hazelcast vs. Sphinx

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Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSKey-value storeSearch engine
Secondary database modelsDocument store
Spatial DBMS
Document store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitegreenplum.orghazelcast.comsphinxsearch.com
Technical documentationdocs.greenplum.orghazelcast.org/­imdg/­docssphinxsearch.com/­docs
DeveloperPivotal Software Inc.HazelcastSphinx Technologies Inc.
Initial release200520082001
Current release7.0.0, September 20235.3.6, November 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinuxAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesno
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.yes infosince Version 4.2yes infothe object must implement a serialization strategy
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol
Supported programming languagesC
Java
Perl
Python
R
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesno
Triggersyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes 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.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlno

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