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DBMS > Ignite vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Spark SQL vs. TiDB

System Properties Comparison Ignite vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Spark SQL vs. TiDB

Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTiDB  Xexclude from comparison
DescriptionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLSpark SQL is a component on top of 'Spark Core' for structured data processingTiDB 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.
Primary database modelKey-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMSRelational DBMS
Secondary database modelsDocument 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 infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score4.25
Rank#74  Overall
#40  Relational DBMS
Websiteignite.apache.orgazure.microsoft.com/­services/­data-explorerwww.postgresql.orgspark.apache.org/­sqlpingcap.com
Technical documentationapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.pingcap.com/­tidb/­stable
DeveloperApache Software FoundationMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software FoundationPingCAP, Inc.
Initial release201520191989 info1989: Postgres, 1996: PostgreSQL20142016
Current releaseApache Ignite 2.6cloud service with continuous releases16.3, May 20243.5.0 ( 2.13), September 20238.1.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoBSDOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetCScalaGo, Rust
Server operating systemsLinux
OS X
Solaris
Windows
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Windows
Linux
Data schemeyesFixed 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.yesyesyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesall fields are automatically indexedyesnoyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensionsSQL-like DML and DDL statementsyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
GORM
JDBC
ODBC
Proprietary protocol
SQLAlchemy
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersyes (cache interceptors and events)yes 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 servicepartitioning by range, list and (since PostgreSQL 11) by hashyes, utilizing Spark Corehorizontal partitioning (by key range)
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensionsnoneUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes infowith TiSpark Connector
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes infofull support since version 6.6
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
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.yesnononono
User concepts infoAccess controlSecurity Hooks for custom implementationsAzure Active Directory Authenticationfine grained access rights according to SQL-standardnoFine grained access rights according to SQL-standard
More information provided by the system vendor
IgniteMicrosoft Azure Data ExplorerPostgreSQLSpark SQLTiDB
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...
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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...
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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...
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More resources
IgniteMicrosoft Azure Data ExplorerPostgreSQLSpark SQLTiDB
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