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DBMS > Citus vs. Datastax Enterprise vs. EXASOL vs. Microsoft Azure Data Explorer vs. Netezza

System Properties Comparison Citus vs. Datastax Enterprise vs. EXASOL vs. Microsoft Azure Data Explorer vs. Netezza

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonEXASOL  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Fully managed big data interactive analytics platformData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSWide column storeRelational DBMSRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score5.80
Rank#60  Overall
#4  Wide column stores
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitewww.citusdata.comwww.datastax.com/­products/­datastax-enterprisewww.exasol.comazure.microsoft.com/­services/­data-explorerwww.ibm.com/­products/­netezza
Technical documentationdocs.citusdata.comdocs.datastax.comwww.exasol.com/­resourcesdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDataStaxExasolMicrosoftIBM
Initial release20102011200020192000
Current release8.1, December 20186.8, April 2020cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialcommercialcommercial
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.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageCJava
Server operating systemsLinuxLinux
OS X
hostedLinux infoincluded in appliance
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes 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 infospecific XML type available, but no XML query functionalitynonoyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like DML and DDL statements (CQL); Spark SQLyesKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
.Net
JDBC
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
OLE DB
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nouser defined functionsYes, possible languages: KQL, Python, Ryes
Triggersyesyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"ShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsconfigurable replication factor, datacenter aware, advanced replication for edge computingyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoHadoop integrationSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoAtomicity and isolation are supported for single operationsACIDnoACID
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.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per objectAccess rights for users, groups and roles according to SQL-standardAzure Active Directory AuthenticationUsers with fine-grained authorization concept
More information provided by the system vendor
CitusDatastax EnterpriseEXASOLMicrosoft Azure Data ExplorerNetezza infoAlso called PureData System for Analytics by IBM
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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CitusDatastax EnterpriseEXASOLMicrosoft Azure Data ExplorerNetezza infoAlso called PureData System for Analytics by IBM
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