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DBMS > AlaSQL vs. EJDB vs. Faircom EDGE vs. HBase vs. Splice Machine

System Properties Comparison AlaSQL vs. EJDB vs. Faircom EDGE vs. HBase vs. Splice Machine

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonEJDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHBase  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionJavaScript DBMS libraryEmbeddable 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 environmentsWide-column store based on Apache Hadoop and on concepts of BigTableOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Relational DBMS
Document storeKey-value store
Relational DBMS
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.49
Rank#259  Overall
#40  Document stores
#120  Relational DBMS
Score0.30
Rank#294  Overall
#44  Document stores
Score0.03
Rank#380  Overall
#59  Key-value stores
#157  Relational DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitealasql.orggithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-edgehbase.apache.orgsplicemachine.com
Technical documentationgithub.com/­AlaSQL/­alasqlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhbase.apache.org/­book.htmlsplicemachine.com/­how-it-works
DeveloperAndrey Gershun & Mathias R. WulffSoftmotionsFairCom CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetSplice Machine
Initial release20142012197920082014
Current releaseV3, October 20202.3.4, January 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoMIT-LicenseOpen Source infoGPLv2commercial infoRestricted, free version availableOpen Source infoApache version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptCANSI C, C++JavaJava
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)server-lessAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyes
Typing infopredefined data types such as float or datenoyes infostring, integer, double, bool, date, object_idyes, ANSI Standard SQL Typesoptions to bring your own types, AVROyes
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.noyesno
Secondary indexesnonoyesnoyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.noyes infoANSI SQL queriesnoyes
APIs and other access methodsJavaScript APIin-process shared libraryADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJavaScriptActionscript
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#
C++
Groovy
Java
PHP
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes info.Net, JavaScript, C/C++yes infoCoprocessors in Javayes infoJava
Triggersyesnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneFile partitioning infoCustomizable business rules for partitioningShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno infotypically not needed, however similar functionality with collection joins possibleyes infowhen using SQLnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storagenoACIDSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyes infoacross SQL and NoSQLyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlnonoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles according to SQL-standard

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More resources
AlaSQLEJDBFaircom EDGE infoformerly c-treeEDGEHBaseSplice Machine
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