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DBMS > Ehcache vs. Google Cloud Bigtable vs. GridDB vs. YDB

System Properties Comparison Ehcache vs. Google Cloud Bigtable vs. GridDB vs. YDB

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonYDB  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.Scalable in-memory time series database optimized for IoT and Big DataA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelKey-value storeKey-value store
Wide column store
Time Series DBMSDocument store
Relational DBMS
Secondary database modelsKey-value store
Relational 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
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitewww.ehcache.orgcloud.google.com/­bigtablegriddb.netgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationwww.ehcache.org/­documentationcloud.google.com/­bigtable/­docsdocs.griddb.netydb.tech/­en/­docs
DeveloperTerracotta Inc, owned by Software AGGoogleToshiba CorporationYandex
Initial release2009201520132019
Current release3.10.0, March 20225.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0; 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 languageJavaC++
Server operating systemsAll OS with a Java VMhostedLinuxLinux
Data schemeschema-freeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesnoyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nononono
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (YQL)
APIs and other access methodsJCachegRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesJavaC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnononono
Triggersyes infoCache Event Listenersnoyes
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 ServerInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
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 within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceAtomic single-row operationsACID at container levelACID
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.yesnoyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseAccess rights defined for Yandex Cloud users
More information provided by the system vendor
EhcacheGoogle Cloud BigtableGridDBYDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
EhcacheGoogle Cloud BigtableGridDBYDB
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