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DBMS > Hazelcast vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB vs. Yanza

System Properties Comparison Hazelcast vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB vs. Yanza

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA widely adopted in-memory data gridWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBTime Series DBMS for IoT Applications
Primary database modelKey-value storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSKey-value storeTime Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.97
Rank#57  Overall
#6  Key-value stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitehazelcast.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­bytedance/­terarkdbyanza.com
Technical documentationhazelcast.org/­imdg/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperHazelcastOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationByteDance, originally TerarkYanza
Initial release20081994201420162015
Current release5.3.6, November 202318.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infocommercial license availableOpen Source infoApache 2.0commercial inforestricted open source version availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)ScalaC++
Server operating systemsAll OS with a Java VMAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Windows
Data schemeschema-freeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesnono
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 infothe object must implement a serialization strategyyes infoonly with the Berkeley DB XML editionnonono
Secondary indexesyesyesnonono
SQL infoSupport of SQLSQL-like query languageyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsnono
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
C++ API
Java API
HTTP API
Supported programming languages.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
Java
Python
R
Scala
C++
Java
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesnononono
Triggersyes infoEventsyes infoonly for the SQL APInonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapSource-replica replicationnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlRole-based access controlnononono

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More resources
HazelcastOracle Berkeley DBSpark SQLTerarkDBYanza
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