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DBMS > Ehcache vs. Geode vs. Google Cloud Datastore vs. GridGain

System Properties Comparison Ehcache vs. Geode vs. Google Cloud Datastore vs. GridGain

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelKey-value storeKey-value storeDocument storeColumnar
Key-value store
Object oriented DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.79
Rank#66  Overall
#8  Key-value stores
Score1.51
Rank#147  Overall
#25  Key-value stores
Score4.13
Rank#71  Overall
#12  Document stores
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Websitewww.ehcache.orggeode.apache.orgcloud.google.com/­datastorewww.gridgain.com
Technical documentationwww.ehcache.org/­documentationgeode.apache.org/­docscloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.html
DeveloperTerracotta Inc, owned by Software AGOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleGridGain Systems, Inc.
Initial release2009200220082007
Current release3.10.0, March 20221.1, February 2017GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercial, open source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava, C++, .Net, Python, REST, SQL
Server operating systemsAll OS with a Java VMAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
OS X
Solaris
Windows
z/OS
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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.nononoyes
Secondary indexesnonoyesyes
SQL infoSupport of SQLnoSQL-like query language (OQL)SQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJCacheJava Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesJava.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functionsusing Google App Engineyes (compute grid and cache interceptors can be used instead)
Triggersyes infoCache Event Listenersyes infoCache Event ListenersCallbacks using the Google Apps Engineyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerMulti-source replicationMulti-source replication using Paxosyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceyes, on a single nodeACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyesnoyes
User concepts infoAccess controlnoAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control
Security Hooks for custom implementations

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More resources
EhcacheGeodeGoogle Cloud DatastoreGridGain
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