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DBMS > Hazelcast vs. Prometheus vs. Sadas Engine vs. Splice Machine vs. UniData,UniVerse

System Properties Comparison Hazelcast vs. Prometheus vs. Sadas Engine vs. Splice Machine vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonPrometheus  Xexclude from comparisonSadas Engine  Xexclude from comparisonSplice Machine  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionA widely adopted in-memory data gridOpen-source Time Series DBMS and monitoring systemSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelKey-value storeTime Series DBMSRelational DBMSRelational DBMSMultivalue DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score2.85
Rank#98  Overall
#1  Multivalue DBMS
Websitehazelcast.comprometheus.iowww.sadasengine.comsplicemachine.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationhazelcast.org/­imdg/­docsprometheus.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsplicemachine.com/­how-it-worksdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperHazelcastSADAS s.r.l.Splice MachineRocket Software
Initial release20082015200620141985
Current release5.3.6, November 20238.03.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercial infofree trial version availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++JavaC
Server operating systemsAll OS with a Java VMLinux
Windows
AIX
Linux
Windows
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyesoptional
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 infoImport of XML data possibleno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyesyesyes
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP/JSON APIJDBC
ODBC
Proprietary protocol
JDBC
Native Spark Datasource
ODBC
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesnonoyes infoJavayes
Triggersyes infoEventsnonoyesyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes infoby FederationnoneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACIDACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infomanaged by 'Learn by Usage'yes
User concepts infoAccess controlRole-based access controlnoAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAccess rights according to SQL-standard and operating system based

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More resources
HazelcastPrometheusSadas EngineSplice MachineUniData,UniVerse
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