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DBMS > Badger vs. Citus vs. Faircom EDGE vs. Splice Machine vs. Sqrrl

System Properties Comparison Badger vs. Citus vs. Faircom EDGE vs. Splice Machine vs. Sqrrl

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonCitus  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSplice Machine  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value storeRelational DBMSKey-value store
Relational DBMS
Relational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.citusdata.comwww.faircom.com/­products/­faircom-edgesplicemachine.comsqrrl.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.citusdata.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsplicemachine.com/­how-it-works
DeveloperDGraph LabsFairCom CorporationSplice MachineAmazon infooriginally Sqrrl Data, Inc.
Initial release20172010197920142012
Current release8.1, December 2018V3, October 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL, commercial license also availablecommercial infoRestricted, free version availableOpen 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 languageGoCANSI C, C++JavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or datenoyesyes, ANSI Standard SQL Typesyesyes
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.noyes infospecific XML type available, but no XML query functionalityyes
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsyes infoANSI SQL queriesyesno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGo.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes info.Net, JavaScript, C/C++yes infoJavano
Triggersnoyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingFile partitioning infoCustomizable business rules for partitioningShared Nothhing Auto-Sharding, Columnar PartitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infoother methods possible by using 3rd party extensionsyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication
Source-replica replication
selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesyes infowhen using SQLyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles according to SQL-standardCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
BadgerCitusFaircom EDGE infoformerly c-treeEDGESplice MachineSqrrl
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