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DBMS > Hazelcast vs. Hive vs. JSqlDb vs. Microsoft Azure Data Explorer vs. SingleStore

System Properties Comparison Hazelcast vs. Hive vs. JSqlDb vs. Microsoft Azure Data Explorer vs. SingleStore

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHive  Xexclude from comparisonJSqlDb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionA widely adopted in-memory data griddata warehouse software for querying and managing large distributed datasets, built on HadoopJavaScript Query Language Database, stores JavaScript objects and primitivesFully managed big data interactive analytics platformMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelKey-value storeRelational DBMSDocument store
Object oriented DBMS
Relational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.97
Rank#57  Overall
#6  Key-value stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.60
Rank#62  Overall
#35  Relational DBMS
Websitehazelcast.comhive.apache.orgjsqldb.org (offline)azure.microsoft.com/­services/­data-explorerwww.singlestore.com
Technical documentationhazelcast.org/­imdg/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorerdocs.singlestore.com
DeveloperHazelcastApache Software Foundation infoinitially developed by FacebookKonrad von BackstromMicrosoftSingleStore Inc.
Initial release20082012201820192013
Current release5.3.6, November 20233.1.3, April 20220.8, December 2018cloud service with continuous releases8.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2Open Sourcecommercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageJavaJavaC++, Go
Server operating systemsAll OS with a Java VMAll OS with a Java VMLinux
macOS
Windows
hostedLinux info64 bit version required
Data schemeschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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 strategynoyesno
Secondary indexesyesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnoKusto Query Language (KQL), SQL subsetyes infobut no triggers and foreign keys
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
PHP
Python
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyes infouser defined functions and integration of map-reducefunctions in JavaScriptYes, possible languages: KQL, Python, Ryes
Triggersyes infoEventsnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoImplicit feature of the cloud serviceSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapselectable replication factornoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infousing RocksDByesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and rolesAzure Active Directory AuthenticationFine grained access control via users, groups and roles
More information provided by the system vendor
HazelcastHiveJSqlDbMicrosoft Azure Data ExplorerSingleStore infoformer name was MemSQL
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
HazelcastHiveJSqlDbMicrosoft Azure Data ExplorerSingleStore infoformer name was MemSQL
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