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DBMS > Datastax Enterprise vs. Faircom EDGE vs. Kinetica

System Properties Comparison Datastax Enterprise vs. Faircom EDGE vs. Kinetica

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Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFully vectorized database across both GPUs and CPUs
Primary database modelWide column storeKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.80
Rank#60  Overall
#4  Wide column stores
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitewww.datastax.com/­products/­datastax-enterprisewww.faircom.com/­products/­faircom-edgewww.kinetica.com
Technical documentationdocs.datastax.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.kinetica.com
DeveloperDataStaxFairCom CorporationKinetica
Initial release201119792012
Current release6.8, April 2020V3, October 20207.1, August 2021
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaANSI C, C++C, C++
Server operating systemsLinux
OS X
Android
Linux infoARM, x86
Raspbian
Windows
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLyes infoANSI SQL queriesSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++user defined functions
Triggersyesyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"File partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingyes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infowhen using SQLyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users can be defined per objectFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users and roles on table level
More information provided by the system vendor
Datastax EnterpriseFaircom EDGE infoformerly c-treeEDGEKinetica
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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Datastax EnterpriseFaircom EDGE infoformerly c-treeEDGEKinetica
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