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DBMS > BigchainDB vs. Ehcache vs. Fujitsu Enterprise Postgres vs. Heroic vs. Splice Machine

System Properties Comparison BigchainDB vs. Ehcache vs. Fujitsu Enterprise Postgres vs. Heroic vs. Splice Machine

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonEhcache  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHeroic  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA widely adopted Java cache with tiered storage optionsEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeKey-value storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score4.89
Rank#67  Overall
#8  Key-value stores
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.bigchaindb.comwww.ehcache.orgwww.postgresql.fastware.comgithub.com/­spotify/­heroicsplicemachine.com
Technical documentationbigchaindb.readthedocs.io/­en/­latestwww.ehcache.org/­documentationwww.postgresql.fastware.com/­product-manualsspotify.github.io/­heroicsplicemachine.com/­how-it-works
DeveloperTerracotta Inc, owned by Software AGPostgreSQL Global Development Group, Fujitsu Australia Software TechnologySpotifySplice Machine
Initial release2016200920142014
Current release3.10.0, March 2022Fujitsu Enterprise Postgres 14, January 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL v3Open Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonJavaCJavaJava
Server operating systemsLinuxAll OS with a Java VMLinux
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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.nonono
Secondary indexesnoyesyes infovia Elasticsearchyes
SQL infoSupport of SQLnonoyesnoyes
APIs and other access methodsCLI Client
RESTful HTTP API
JCacheADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
Java.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoyes infoJava
Triggersyes infoCache Event Listenersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoby using Terracotta Serverpartitioning by range, list and by hashShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoby using Terracotta ServerSource-replica replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByes 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.yesnoyes
User concepts infoAccess controlyesnofine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
BigchainDBEhcacheFujitsu Enterprise PostgresHeroicSplice Machine
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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BigchainDBEhcacheFujitsu Enterprise PostgresHeroicSplice Machine
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