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DBMS > Faircom DB vs. Faircom EDGE vs. Microsoft Azure AI Search vs. Splice Machine

System Properties Comparison Faircom DB vs. Faircom EDGE vs. Microsoft Azure AI Search vs. Splice Machine

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsSearch-as-a-service for web and mobile app developmentOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Relational DBMS
Key-value store
Relational DBMS
Search engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.24
Rank#311  Overall
#44  Key-value stores
#140  Relational DBMS
Score0.03
Rank#380  Overall
#59  Key-value stores
#157  Relational DBMS
Score5.71
Rank#64  Overall
#8  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbwww.faircom.com/­products/­faircom-edgeazure.microsoft.com/­en-us/­services/­searchsplicemachine.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmllearn.microsoft.com/­en-us/­azure/­searchsplicemachine.com/­how-it-works
DeveloperFairCom CorporationFairCom CorporationMicrosoftSplice Machine
Initial release1979197920152014
Current releaseV12, November 2020V3, October 2020V13.1, March 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercial infoRestricted, free version availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++ANSI C, C++Java
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Android
Linux infoARM, x86
Raspbian
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeschema free, schema optional, schema required, partial schema,Flexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyes, 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.noyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsyes infoANSI SQL queriesnoyes
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
Java
JavaScript
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes info.Net, JavaScript, C/C++noyes infoJava
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningFile partitioning infoCustomizable business rules for partitioningSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infowhen using SQLnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.yes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
Faircom DB infoformerly c-treeACEFaircom EDGE infoformerly c-treeEDGEMicrosoft Azure AI SearchSplice Machine
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