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DBMS > Faircom EDGE vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Splice Machine vs. VictoriaMetrics

System Properties Comparison Faircom EDGE vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Splice Machine vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSplice Machine  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsWell established RDBMSElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMSTime Series DBMS
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#82  Overall
#44  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websitewww.faircom.com/­products/­faircom-edgewww.actian.com/­databases/­ingresazure.microsoft.com/­services/­synapse-analyticssplicemachine.comvictoriametrics.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.actian.com/­ingresdocs.microsoft.com/­azure/­synapse-analyticssplicemachine.com/­how-it-worksdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperFairCom CorporationActian CorporationMicrosoftSplice MachineVictoriaMetrics
Initial release19791974 infooriginally developed at University Berkely in early 1970s201620142018
Current releaseV3, October 202011.2, May 20223.1, March 2021v1.91, May 2023
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialcommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++CC++JavaGo
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedLinux
OS X
Solaris
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyes, 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 infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infoANSI SQL queriesyesyesyesno
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
ADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yesTransact SQLyes infoJavano
Triggersyesyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioninghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, horizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsIngres ReplicatoryesMulti-source replication
Source-replica replication
Synchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infowhen using SQLyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyes infoMVCCyesyes, 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.yesnoyesno
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.fine grained access rights according to SQL-standardyesAccess rights for users, groups and roles according to SQL-standard

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More resources
Faircom EDGE infoformerly c-treeEDGEIngresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSplice MachineVictoriaMetrics
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