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DBMS > Ehcache vs. Google Cloud Bigtable vs. jBASE vs. Splice Machine

System Properties Comparison Ehcache vs. Google Cloud Bigtable vs. jBASE vs. Splice Machine

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonjBASE  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A robust multi-value DBMS comprising development tools and middlewareOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeKey-value store
Wide column store
Multivalue DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.ehcache.orgcloud.google.com/­bigtablewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasesplicemachine.com
Technical documentationwww.ehcache.org/­documentationcloud.google.com/­bigtable/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9splicemachine.com/­how-it-works
DeveloperTerracotta Inc, owned by Software AGGoogleRocket Software (formerly Zumasys)Splice Machine
Initial release2009201519912014
Current release3.10.0, March 20225.73.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsAll OS with a Java VMhostedAIX
Linux
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnooptionalyes
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.nonoyes
Secondary indexesnonoyes
SQL infoSupport of SQLnonoEmbedded SQL for jBASE in BASICyes
APIs and other access methodsJCachegRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJavaC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Basic
Jabbascript
Java
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesyes infoJava
Triggersyes infoCache Event Listenersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerInternal replication in Colossus, and regional replication between two clusters in different zonesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item levelAccess rights for users, groups and roles according to SQL-standard

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More resources
EhcacheGoogle Cloud BigtablejBASESplice Machine
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