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DBMS > Ehcache vs. Microsoft Azure Table Storage vs. Splice Machine

System Properties Comparison Ehcache vs. Microsoft Azure Table Storage vs. Splice Machine

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsA Wide Column Store for rapid development using massive semi-structured datasetsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.ehcache.orgazure.microsoft.com/­en-us/­services/­storage/­tablessplicemachine.com
Technical documentationwww.ehcache.org/­documentationsplicemachine.com/­how-it-works
DeveloperTerracotta Inc, owned by Software AGMicrosoftSplice Machine
Initial release200920122014
Current release3.10.0, March 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesnonoyes
SQL infoSupport of SQLnonoyes
APIs and other access methodsJCacheRESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesJava.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoJava
Triggersyes infoCache Event Listenersnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serveryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standard

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EhcacheMicrosoft Azure Table StorageSplice Machine
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