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DBMS > EJDB vs. Faircom EDGE vs. HugeGraph vs. Splice Machine vs. Sqrrl

System Properties Comparison EJDB vs. Faircom EDGE vs. HugeGraph vs. Splice Machine vs. Sqrrl

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHugeGraph  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.
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA fast-speed and highly-scalable Graph DBMSOpen-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 modelDocument storeKey-value store
Relational DBMS
Graph DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#294  Overall
#44  Document stores
Score0.03
Rank#380  Overall
#59  Key-value stores
#157  Relational DBMS
Score0.15
Rank#339  Overall
#33  Graph DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-edgegithub.com/­hugegraph
hugegraph.apache.org
splicemachine.comsqrrl.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhugegraph.apache.org/­docssplicemachine.com/­how-it-works
DeveloperSoftmotionsFairCom CorporationBaiduSplice MachineAmazon infooriginally Sqrrl Data, Inc.
Initial release20121979201820142012
Current releaseV3, October 20200.93.1, March 2021
License infoCommercial or Open SourceOpen Source infoGPLv2commercial infoRestricted, free version availableOpen Source infoApache Version 2.0Open 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 languageCANSI C, C++JavaJavaJava
Server operating systemsserver-lessAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
macOS
Unix
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes, ANSI Standard SQL Typesyesyesyes
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.yesno
Secondary indexesnoyesyes infoalso supports composite index and range indexyesyes
SQL infoSupport of SQLnoyes infoANSI SQL queriesnoyesno
APIs and other access methodsin-process shared libraryADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
Native Spark Datasource
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Groovy
Java
Python
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++asynchronous Gremlin script jobsyes infoJavano
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning infoCustomizable business rules for partitioningyes infodepending on used storage backend, e.g. Cassandra and HBaseShared 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 logsyes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replication
Source-replica replication
selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonovia hugegraph-sparkYes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Eventual ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyes infowhen using SQLyes infoedges in graphyesno
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 datayes infoRead/Write Lockingyes 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.yesyesyes
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Users, roles and permissionsAccess 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
EJDBFaircom EDGE infoformerly c-treeEDGEHugeGraphSplice MachineSqrrl
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