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DBMS > BigchainDB vs. etcd vs. HBase vs. Splice Machine vs. TimesTen

System Properties Comparison BigchainDB vs. etcd vs. HBase vs. Splice Machine vs. TimesTen

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonetcd  Xexclude from comparisonHBase  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA distributed reliable key-value storeWide-column store based on Apache Hadoop and on concepts of BigTableOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkIn-Memory RDBMS compatible to Oracle
Primary database modelDocument storeKey-value storeWide column storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score7.25
Rank#54  Overall
#5  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.bigchaindb.cometcd.io
github.com/­etcd-io/­etcd
hbase.apache.orgsplicemachine.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationbigchaindb.readthedocs.io/­en/­latestetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hbase.apache.org/­book.htmlsplicemachine.com/­how-it-worksdocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetSplice MachineOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2016200820141998
Current release3.4, August 20192.3.4, January 20213.1, March 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoAGPL v3Open Source infoApache Version 2.0Open Source infoApache version 2Open Source infoAGPL 3.0, commercial license availablecommercial
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 languagePythonGoJavaJava
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeschema-freeschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or datenonooptions to bring your own types, AVROyesyes
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 SQLnononoyesyes
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC
JSON over HTTP
Java API
RESTful HTTP API
Thrift
JDBC
Native Spark Datasource
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayes infoJavaPL/SQL
Triggersyes, watching key changesyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)ACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlyesnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
BigchainDBetcdHBaseSplice MachineTimesTen
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