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DBMS > Badger vs. BigchainDB vs. CockroachDB vs. HEAVY.AI vs. Splice Machine

System Properties Comparison Badger vs. BigchainDB vs. CockroachDB vs. HEAVY.AI vs. Splice Machine

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBigchainDB  Xexclude from comparisonCockroachDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.BigchainDB is scalable blockchain database offering decentralization, immutability and native assetsCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeDocument storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#325  Overall
#49  Key-value stores
Score0.82
Rank#212  Overall
#36  Document stores
Score6.10
Rank#58  Overall
#33  Relational DBMS
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.bigchaindb.comwww.cockroachlabs.comgithub.com/­heavyai/­heavydb
www.heavy.ai
splicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerbigchaindb.readthedocs.io/­en/­latestwww.cockroachlabs.com/­docsdocs.heavy.aisplicemachine.com/­how-it-works
DeveloperDGraph LabsCockroach LabsHEAVY.AI, Inc.Splice Machine
Initial release20172016201520162014
Current release23.1.1, May 20235.10, January 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL v3Open Source infoApache 2.0, commercial license availableOpen Source infoApache Version 2; enterprise edition availableOpen 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 languageGoPythonGoC++ and CUDAJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxLinux
macOS
Windows
LinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freedynamic schemayesyes
Typing infopredefined data types such as float or datenonoyesyesyes
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 indexesnoyesnoyes
SQL infoSupport of SQLnonoyes, wire compatible with PostgreSQLyesyes
APIs and other access methodsCLI Client
RESTful HTTP API
JDBCJDBC
ODBC
Thrift
Vega
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGoGo
Haskell
Java
JavaScript
Python
Ruby
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
All languages supporting JDBC/ODBC/Thrift
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnononoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTSharding infoRound robinShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorMulti-source replication using RAFTMulti-source replicationMulti-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 systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnoyesRole-based access controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
BadgerBigchainDBCockroachDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Splice Machine
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