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DBMS > Badger vs. BigchainDB vs. Faircom DB vs. HEAVY.AI vs. Splice Machine

System Properties Comparison Badger vs. BigchainDB vs. Faircom DB vs. HEAVY.AI vs. Splice Machine

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBigchainDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  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 assetsNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.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 storeKey-value store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.79
Rank#212  Overall
#36  Document stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.bigchaindb.comwww.faircom.com/­products/­faircom-dbgithub.com/­heavyai/­heavydb
www.heavy.ai
splicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerbigchaindb.readthedocs.io/­en/­latestdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.heavy.aisplicemachine.com/­how-it-works
DeveloperDGraph LabsFairCom CorporationHEAVY.AI, Inc.Splice Machine
Initial release20172016197920162014
Current releaseV12, November 20205.10, January 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL v3commercial infoRestricted, free version 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 languageGoPythonANSI C, C++C++ and CUDAJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema free, schema optional, schema required, partial schema,yesyes
Typing infopredefined data types such as float or datenonoyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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, ANSI SQL with proprietary extensionsyesyes
APIs and other access methodsCLI Client
RESTful HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
Thrift
Vega
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGoGo
Haskell
Java
JavaScript
Python
Ruby
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
All languages supporting JDBC/ODBC/Thrift
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++noyes infoJava
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoRound robinShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factoryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-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 systemnoneEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDBYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlnoyesFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
BadgerBigchainDBFaircom DB infoformerly c-treeACEHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Splice Machine
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