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DBMS > Faircom EDGE vs. Microsoft Azure Data Explorer vs. Sphinx vs. Splice Machine vs. TerarkDB

System Properties Comparison Faircom EDGE vs. Microsoft Azure Data Explorer vs. Sphinx vs. Splice Machine vs. TerarkDB

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelKey-value store
Relational DBMS
Relational DBMS infocolumn orientedSearch engineRelational DBMSKey-value store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.08
Rank#367  Overall
#56  Key-value stores
Websitewww.faircom.com/­products/­faircom-edgeazure.microsoft.com/­services/­data-explorersphinxsearch.comsplicemachine.comgithub.com/­bytedance/­terarkdb
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docssplicemachine.com/­how-it-worksbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperFairCom CorporationMicrosoftSphinx Technologies Inc.Splice MachineByteDance, originally Terark
Initial release19792019200120142016
Current releaseV3, October 2020cloud service with continuous releases3.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++C++JavaC++
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)yesyesschema-free
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyesno
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.yesyesno
Secondary indexesyesall fields are automatically indexedyes infofull-text index on all search fieldsyesno
SQL infoSupport of SQLyes infoANSI SQL queriesKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)yesno
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
C++ API
Java API
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, Rnoyes infoJavano
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesno
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Azure Active Directory AuthenticationnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
Faircom EDGE infoformerly c-treeEDGEMicrosoft Azure Data ExplorerSphinxSplice MachineTerarkDB
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