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DBMS > Hazelcast vs. Netezza vs. STSdb vs. Vertica

System Properties Comparison Hazelcast vs. Netezza vs. STSdb vs. Vertica

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSTSdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA widely adopted in-memory data gridData warehouse and analytics appliance part of IBM PureSystemsKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelKey-value storeRelational DBMSKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.97
Rank#57  Overall
#6  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitehazelcast.comwww.ibm.com/­products/­netezzagithub.com/­STSSoft/­STSdb4www.vertica.com
Technical documentationhazelcast.org/­imdg/­docsvertica.com/­documentation
DeveloperHazelcastIBMSTS Soft SCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2008200020112005
Current release5.3.6, November 20234.0.8, September 201512.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoGPLv2, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#C++
Server operating systemsAll OS with a Java VMLinux infoincluded in applianceWindowsLinux
Data schemeschema-freeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyes infoprimitive types and user defined types (classes)yes
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.yes infothe object must implement a serialization strategyno
Secondary indexesyesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageyesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
OLE DB
.NET Client APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
C#
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoEventsnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapSource-replica replicationnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACIDnoACID
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.yesno
User concepts infoAccess controlRole-based access controlUsers with fine-grained authorization conceptnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HazelcastNetezza infoAlso called PureData System for Analytics by IBMSTSdbVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
HazelcastNetezza infoAlso called PureData System for Analytics by IBMSTSdbVertica infoOpenText™ Vertica™
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