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

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

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHypertable  Xexclude from comparisonSplice Machine  Xexclude from comparisonSqrrl  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.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.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsAn open source BigTable implementation based on distributed file systems such as HadoopOpen-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 storeKey-value store
Relational DBMS
Wide column storeRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
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.faircom.com/­products/­faircom-edgesplicemachine.comsqrrl.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsplicemachine.com/­how-it-works
DeveloperDGraph LabsFairCom CorporationHypertable Inc.Splice MachineAmazon infooriginally Sqrrl Data, Inc.
Initial release20171979200920142012
Current releaseV3, October 20200.9.8.11, March 20163.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoRestricted, free version availableOpen Source infoGNU version 3. Commercial license 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

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Implementation languageGoANSI C, C++C++JavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Android
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or datenoyes, ANSI Standard SQL Typesnoyesyes
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
Secondary indexesnoyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLnoyes infoANSI SQL queriesnoyesno
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
C++ API
Thrift
JDBC
Native Spark Datasource
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGoC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C++
Java
Perl
PHP
Python
Ruby
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 proceduresnoyes info.Net, JavaScript, C/C++noyes infoJavano
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning infoCustomizable business rules for partitioningShardingShared Nothhing Auto-Sharding, Columnar PartitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factor on file system levelMulti-source replication
Source-replica replication
selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyes infowhen using SQLnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes, 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.noyesyes
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.noAccess 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
BadgerFaircom EDGE infoformerly c-treeEDGEHypertableSplice MachineSqrrl
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