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

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

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonEJDB  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.
DescriptionAnalytic DBMS for real-time computations and queriesEmbeddable 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 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 modelRelational DBMS infoa hierachical model (tree) can be imposedDocument storeKey-value store
Relational DBMS
Relational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#342  Overall
#150  Relational DBMS
Score0.30
Rank#294  Overall
#44  Document stores
Score0.03
Rank#380  Overall
#59  Key-value stores
#157  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitebigobject.iogithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-edgesplicemachine.comsqrrl.com
Technical documentationdocs.bigobject.iogithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsplicemachine.com/­how-it-works
DeveloperBigObject, Inc.SoftmotionsFairCom CorporationSplice MachineAmazon infooriginally Sqrrl Data, Inc.
Initial release20152012197920142012
Current releaseV3, October 20203.1, March 2021
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoGPLv2commercial 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

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Implementation languageCANSI C, C++JavaJava
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
server-lessAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes, 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
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoANSI SQL queriesyesno
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
in-process shared libraryADO.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 languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
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 proceduresLuanoyes info.Net, JavaScript, C/C++yes infoJavano
Triggersnonoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneFile partitioning infoCustomizable business rules for partitioningShared Nothhing Auto-Sharding, Columnar PartitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneyes 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 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 integrityyes infoautomatically between fact table and dimension tablesno infotypically not needed, however similar functionality with collection joins possibleyes infowhen using SQLyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yes infoRead/Write Lockingyes 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.yesyesyes
User concepts infoAccess controlnonoFine 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
BigObjectEJDBFaircom EDGE infoformerly c-treeEDGESplice MachineSqrrl
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