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DBMS > Datastax Enterprise vs. Ignite vs. Kinetica

System Properties Comparison Datastax Enterprise vs. Ignite vs. Kinetica

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Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonIgnite  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.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.GPU-accelerated database for real-time analysis of large and streaming datasets
Primary database modelWide column storeKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.15
Rank#42  Overall
#4  Wide column stores
Score4.45
Rank#68  Overall
#11  Key-value stores
#37  Relational DBMS
Score0.53
Rank#199  Overall
#97  Relational DBMS
Websitewww.datastax.com/­products/­datastax-enterpriseignite.apache.orgwww.kinetica.com
Technical documentationdocs.datastax.comapacheignite.readme.io/­docswww.kinetica.com/­docs
DeveloperDataStaxApache Software FoundationKinetica
Initial release201120152012
Current release6.7, December 2018Apache Ignite 2.66.0
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, .NetC, C++
Server operating systemsLinux
OS X
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 SQLANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
HDFS API
Hibernate
JCache
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)user defined functions
Triggersyesyes (cache interceptors and events)yes 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"ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingyes (replicated cache)Master-slave replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes
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 datayesyesyes
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 objectSecurity Hooks for custom implementationsAccess rights for users and roles on table level
More information provided by the system vendor
Datastax EnterpriseIgniteKinetica
Specific characteristics100% continuous availability, real-time, distributed, massive scale data management...
» more
Competitive advantagesSupporting the following application requirements: Contextual: complete data layer...
» more
Typical application scenariosApplications that must serve contextual information and be always-on, distributed,...
» 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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More resources
Datastax EnterpriseIgniteKinetica
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