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DBMS > eXtremeDB vs. Hazelcast vs. Oracle Berkeley DB vs. Sphinx

System Properties Comparison eXtremeDB vs. Hazelcast vs. Oracle Berkeley DB vs. Sphinx

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Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonHazelcast  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringA widely adopted in-memory data gridWidely used in-process key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
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
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.mcobject.comhazelcast.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.com
Technical documentationwww.mcobject.com/­docs/­extremedb.htmhazelcast.org/­imdg/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docs
DeveloperMcObjectHazelcastOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.
Initial release2001200819942001
Current release8.2, 20215.3.6, November 202318.1.40, May 20203.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infocommercial license availableOpen 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 languageC and C++JavaC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
All OS with a Java VMAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
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.no infosupport of XML interfaces availableyes infothe object must implement a serialization strategyyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes infowith the option: eXtremeSQLSQL-like query languageyes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesnono
Triggersyes infoby defining eventsyes infoEventsyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes infoReplicated MapSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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 controlRole-based access controlnono
More information provided by the system vendor
eXtremeDBHazelcastOracle Berkeley DBSphinx
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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eXtremeDBHazelcastOracle Berkeley DBSphinx
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