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DBMS > EDB Postgres vs. Ignite vs. Microsoft Azure Data Explorer vs. RavenDB vs. Sphinx

System Properties Comparison EDB Postgres vs. Ignite vs. Microsoft Azure Data Explorer vs. RavenDB vs. Sphinx

Editorial information provided by DB-Engines
NameEDB Postgres  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRavenDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Apache 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 platformOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedDocument storeSearch engine
Secondary database modelsDocument store
Spatial DBMS
Document 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
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.enterprisedb.comignite.apache.orgazure.microsoft.com/­services/­data-explorerravendb.netsphinxsearch.com
Technical documentationwww.enterprisedb.com/­docsapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerravendb.net/­docssphinxsearch.com/­docs
DeveloperEnterpriseDBApache Software FoundationMicrosoftHibernating RhinosSphinx Technologies Inc.
Initial release20052015201920102001
Current release14, December 2021Apache Ignite 2.6cloud service with continuous releases5.4, July 20223.5.1, February 2023
License infoCommercial or Open Sourcecommercial infoBSD for PostgreSQL-componentsOpen Source infoApache 2.0commercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoGPL version 2, commercial licence 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.
Implementation languageCC++, Java, .NetC#C++
Server operating systemsLinux
Windows
Linux
OS X
Solaris
Windows
hostedLinux
macOS
Raspberry Pi
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-freeyes
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-typesnono
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 infospecific XML-type available, but no XML query functionality.yesyes
Secondary indexesyesyesall fields are automatically indexedyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard with numerous extensionsANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetSQL-like query language (RQL)SQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, Ryesno
Triggersyesyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoby hash, list or rangeShardingSharding infoImplicit feature of the cloud serviceShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsAzure Active Directory AuthenticationAuthorization levels configured per client per databaseno

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More resources
EDB PostgresIgniteMicrosoft Azure Data ExplorerRavenDBSphinx
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