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DBMS > Datastax Enterprise vs. Hazelcast vs. Linter vs. Netezza

System Properties Comparison Datastax Enterprise vs. Hazelcast vs. Linter vs. Netezza

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Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonHazelcast  Xexclude from comparisonLinter  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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.A widely adopted in-memory data gridRDBMS for high security requirementsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelWide column storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Document store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.80
Rank#60  Overall
#4  Wide column stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitewww.datastax.com/­products/­datastax-enterprisehazelcast.comlinter.ruwww.ibm.com/­products/­netezza
Technical documentationdocs.datastax.comhazelcast.org/­imdg/­docs
DeveloperDataStaxHazelcastrelex.ruIBM
Initial release2011200819902000
Current release6.8, April 20205.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
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 languageJavaJavaC and C++
Server operating systemsLinux
OS X
All OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux infoincluded in appliance
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLSQL-like query languageyesyes
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQLyes
Triggersyesyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"ShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingyes infoReplicated MapSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoyes
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 or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsone or two-phase-commit; repeatable reads; read commitedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users can be defined per objectRole-based access controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept
More information provided by the system vendor
Datastax EnterpriseHazelcastLinterNetezza infoAlso called PureData System for Analytics by IBM
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 EnterpriseHazelcastLinterNetezza infoAlso called PureData System for Analytics by IBM
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