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DBMS > Ehcache vs. Google Cloud Bigtable vs. Lovefield vs. Teradata Aster

System Properties Comparison Ehcache vs. Google Cloud Bigtable vs. Lovefield vs. Teradata Aster

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonLovefield  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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.Embeddable relational database for web apps written in pure JavaScriptPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeKey-value store
Wide column store
Relational 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
Score0.33
Rank#286  Overall
#131  Relational DBMS
Websitewww.ehcache.orgcloud.google.com/­bigtablegoogle.github.io/­lovefield
Technical documentationwww.ehcache.org/­documentationcloud.google.com/­bigtable/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperTerracotta Inc, owned by Software AGGoogleGoogleTeradata
Initial release2009201520142005
Current release3.10.0, March 20222.1.12, February 2017
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScript
Server operating systemsAll OS with a Java VMhostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
Data schemeschema-freeschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesnoyesyes
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 infoin Aster File Store
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonoSQL-like query language infovia JavaScript builder patternyes
APIs and other access methodsJCachegRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesJavaC#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScriptC
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnononoR packages
Triggersyes infoCache Event ListenersnoUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingnoneSharding
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 zonesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes infoSQL Map-Reduce Framework
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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
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
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infousing MemoryDBno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
EhcacheGoogle Cloud BigtableLovefieldTeradata Aster
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