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DBMS > Hazelcast vs. Microsoft Azure Table Storage vs. Splice Machine vs. Typesense

System Properties Comparison Hazelcast vs. Microsoft Azure Table Storage vs. Splice Machine vs. Typesense

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSplice Machine  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionA widely adopted in-memory data gridA Wide Column Store for rapid development using massive semi-structured datasetsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelKey-value storeWide column storeRelational DBMSSearch engine
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
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.76
Rank#219  Overall
#14  Search engines
Websitehazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tablessplicemachine.comtypesense.org
Technical documentationhazelcast.org/­imdg/­docssplicemachine.com/­how-it-workstypesense.org/­docs
DeveloperHazelcastMicrosoftSplice Machine
Initial release2008201220142015
Current release5.3.6, November 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-freeyesschema-free infopre-defined schema optional
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.yes infothe object must implement a serialization strategyno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenoyesno
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesnoyes infoJavano
Triggersyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
Multi-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedoptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.yesnoyesyes
User concepts infoAccess controlRole-based access controlAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standard

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More resources
HazelcastMicrosoft Azure Table StorageSplice MachineTypesense
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