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DBMS > GBase vs. Hazelcast vs. Microsoft Azure Data Explorer vs. OpenMLDB vs. SingleStore

System Properties Comparison GBase vs. Hazelcast vs. Microsoft Azure Data Explorer vs. OpenMLDB vs. SingleStore

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOpenMLDB  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A widely adopted in-memory data gridFully managed big data interactive analytics platformAn open-source machine learning database that provides a feature platform for training and inferenceMySQL 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 modelRelational DBMSKey-value storeRelational DBMS infocolumn orientedTime Series DBMSRelational 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
Relational DBMSDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.10
Rank#359  Overall
#36  Time Series DBMS
Score5.38
Rank#62  Overall
#35  Relational DBMS
Websitewww.gbase.cnhazelcast.comazure.microsoft.com/­services/­data-exploreropenmldb.aiwww.singlestore.com
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-exploreropenmldb.ai/­docs/­zh/­maindocs.singlestore.com
DeveloperGeneral Data Technology Co., Ltd.HazelcastMicrosoft4 Paradigm Inc.SingleStore Inc.
Initial release20042008201920202013
Current releaseGBase 8a, GBase 8s, GBase 8c5.3.6, November 2023cloud service with continuous releases2024-2 February 20248.5, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Sourcecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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 languageC, Java, PythonJavaC++, Java, ScalaC++, Go
Server operating systemsLinuxAll OS with a Java VMhostedLinuxLinux info64 bit version required
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)Fixed schemayes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.yesyes infothe object must implement a serialization strategyyesnono
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLStandard with numerous extensionsSQL-like query languageKusto Query Language (KQL), SQL subsetyesyes infobut no triggers and foreign keys
APIs and other access methodsADO.NET
C API
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
SQLAlchemy
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesC#.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
Python
Scala
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rnoyes
Triggersyesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark 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 ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes 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.yesnoyesyes
User concepts infoAccess controlyesRole-based access controlAzure Active Directory Authenticationfine grained access rights according to SQL-standardFine grained access control via users, groups and roles
More information provided by the system vendor
GBaseHazelcastMicrosoft Azure Data ExplorerOpenMLDBSingleStore 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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GBaseHazelcastMicrosoft Azure Data ExplorerOpenMLDBSingleStore infoformer name was MemSQL
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