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DBMS > Faircom EDGE vs. HBase vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. Tkrzw

System Properties Comparison Faircom EDGE vs. HBase vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. Tkrzw

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHBase  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionFairCom 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 BigTableEmbeddable relational database for web apps written in pure JavaScriptElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value store
Relational DBMS
Wide column storeRelational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.faircom.com/­products/­faircom-edgehbase.apache.orggoogle.github.io/­lovefieldazure.microsoft.com/­services/­synapse-analyticsdbmx.net/­tkrzw
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhbase.apache.org/­book.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­azure/­synapse-analytics
DeveloperFairCom CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetGoogleMicrosoftMikio Hirabayashi
Initial release19792008201420162020
Current releaseV3, October 20202.3.4, January 20212.1.12, February 20170.9.3, August 2020
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache version 2Open Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++JavaJavaScriptC++C++
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
Unix
Windows infousing Cygwin
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyesyesschema-free
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesoptions to bring your own types, AVROyesyesno
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.yesnononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infoANSI SQL queriesnoSQL-like query language infovia JavaScript builder patternyesno
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C#
C++
Groovy
Java
PHP
Python
Scala
JavaScriptC#
Java
PHP
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infoCoprocessors in JavanoTransact SQLno
TriggersyesyesUsing read-only observersnono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningShardingnoneSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication
Source-replica replication
noneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infousing MemoryDByes infousing specific database classes
User concepts infoAccess controlFine 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 & ABACnoyesno

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More resources
Faircom EDGE infoformerly c-treeEDGEHBaseLovefieldMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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