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DBMS > Hazelcast vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. TiDB vs. Trafodion

System Properties Comparison Hazelcast vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. TiDB vs. Trafodion

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonTiDB  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA widely adopted in-memory data gridFully managed big data interactive analytics platformDatabase as a Service offering with high compatibility to Microsoft SQL ServerTiDB is an open source distributed SQL database that supports Hybrid Transactional/Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.Transactional SQL-on-Hadoop DBMS
Primary database modelKey-value storeRelational DBMS infocolumn orientedRelational DBMSRelational 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
Document store
Graph DBMS
Spatial DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score4.66
Rank#70  Overall
#38  Relational DBMS
Websitehazelcast.comazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­products/­azure-sql/­databasepingcap.comtrafodion.apache.org
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­en-us/­azure/­azure-sqldocs.pingcap.com/­tidb/­stabletrafodion.apache.org/­documentation.html
DeveloperHazelcastMicrosoftMicrosoftPingCAP, Inc.Apache Software Foundation, originally developed by HP
Initial release20082019201020162014
Current release5.3.6, November 2023cloud service with continuous releasesV128.0.0, March 20242.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
TiDB Cloud: Fully-managed TiDB Service. Bring everything great about TiDB to the cloud.
Implementation languageJavaC++Go, RustC++, Java
Server operating systemsAll OS with a Java VMhostedhostedLinuxLinux
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesyesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyes
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 strategyyesyesnono
Secondary indexesyesall fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetyesyesyes
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
GORM
JDBC
ODBC
Proprietary protocol
SQLAlchemy
ADO.NET
JDBC
ODBC
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, RTransact SQLnoJava Stored Procedures
Triggersyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning (by key range)Sharding
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.yes, with always 3 replicas availableUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes infowith TiSpark Connectoryes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes infofull support since version 6.6yes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnonono
User concepts infoAccess controlRole-based access controlAzure Active Directory Authenticationfine grained access rights according to SQL-standardFine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
HazelcastMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureTiDBTrafodion
Specific characteristicsTiDB is an advanced open-source, distributed SQL database for modern application...
» more
Competitive advantages- HORIZONTAL SCALING : TiDB grants total transparency into your data workloads without...
» more
Typical application scenariosTiDB is ideal for transactional applications that require extreme scalability and...
» more
Key customersBlock, Pinterest, Catalyst, Bolt, Flipkart, Capcom, Shopee (E-commerce), JD Cloud...
» more
Market metrics34K+ GitHub stars 5K+ members in TiDB Community Slack 1K+ community contributors...
» more
Licensing and pricing modelsTiDB Community : Free open source software (Apache 2.0) TiDB Self-Hosted : Enterprise...
» more

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HazelcastMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureTiDBTrafodion
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