DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Datastax Enterprise vs. eXtremeDB vs. Microsoft Azure Data Explorer vs. Oracle vs. Sphinx

System Properties Comparison Datastax Enterprise vs. eXtremeDB vs. Microsoft Azure Data Explorer vs. Oracle vs. Sphinx

Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisoneXtremeDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionDataStax 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.Natively in-memory DBMS with options for persistency, high-availability and clusteringFully managed big data interactive analytics platformWidely used RDBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelWide column storeRelational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedRelational DBMSSearch engine
Secondary database modelsDocument 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
Document store
Graph DBMS infowith Oracle Spatial and Graph
RDF store infowith Oracle Spatial and Graph
Spatial DBMS infowith Oracle Spatial and Graph
Vector DBMS infosince Oracle 23
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.93
Rank#56  Overall
#4  Wide column stores
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1244.08
Rank#1  Overall
#1  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.datastax.com/­products/­datastax-enterprisewww.mcobject.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­databasesphinxsearch.com
Technical documentationdocs.datastax.comwww.mcobject.com/­docs/­extremedb.htmdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­databasesphinxsearch.com/­docs
DeveloperDataStaxMcObjectMicrosoftOracleSphinx Technologies Inc.
Initial release20112001201919802001
Current release6.8, April 20208.2, 2021cloud service with continuous releases23c, September 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial inforestricted free version is 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.
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 languageJavaC and C++C and C++C++
Server operating systemsLinux
OS X
AIX
HP-UX
Linux
macOS
Solaris
Windows
hostedAIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes infoSchemaless in JSON and XML columnsyes
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-typesyesno
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.nono infosupport of XML interfaces availableyesyes
Secondary indexesyesyesall fields are automatically indexedyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLyes infowith the option: eXtremeSQLKusto Query Language (KQL), SQL subsetyes infowith proprietary extensionsSQL-like query language (SphinxQL)
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary protocol
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, RPL/SQL infoalso stored procedures in Java possibleno
Triggersyesyes infoby defining eventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"horizontal partitioning / shardingSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan be realized in PL/SQLno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsACIDnoACID infoisolation level can be parameterizedno
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes
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.yesyesnoyes infoVersion 12c introduced the new option 'Oracle Database In-Memory'
User concepts infoAccess controlAccess rights for users can be defined per objectAzure Active Directory Authenticationfine grained access rights according to SQL-standardno
More information provided by the system vendor
Datastax EnterpriseeXtremeDBMicrosoft Azure Data ExplorerOracleSphinx
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
With hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsAnnual subscription
» more
For server use cases, there is a simple per-server license irrespective of the number...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesNavicat for Oracle improves the efficiency and productivity of Oracle developers and administrators with a streamlined working environment.
» more

Devart ODBC driver for Oracle accesses Oracle databases from ODBC-compliant reporting, analytics, BI, and ETL tools on both 32 and 64-bit Windows, macOS, and Linux.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Datastax EnterpriseeXtremeDBMicrosoft Azure Data ExplorerOracleSphinx
DB-Engines blog posts

MySQL is the DBMS of the Year 2019
3 January 2020, Matthias Gelbmann, Paul Andlinger

The struggle for the hegemony in Oracle's database empire
2 May 2017, Paul Andlinger

Architecting eCommerce Platforms for Zero Downtime on Black Friday and Beyond
25 November 2016, Tony Branson (guest author)

show all

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Conferences, events and webinars

Oracle Cloud World
Las Vegas, 9-12 September 2024

Recent citations in the news

DataStax previews new Hyper Converged Data Platform for enterprise AI
15 May 2024, VentureBeat

DataStax Launches New Hyper-Converged Data Platform Giving Enterprises the Complete Modern Data Center Suite ...
15 May 2024, businesswire.com

How to Migrate From DataStax Enterprise to Instaclustr Managed Apache Cassandra
17 January 2024, Database Trends and Applications

DataStax goes vector searching with Astra DB – Blocks and Files
20 July 2023, Blocks and Files

DataStax Rolls Out Vector Search for Astra DB to Support Gen AI
18 July 2023, Datanami

provided by Google News

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

McObject Delivers eXtremeDB 8.4 Improving Performance, Security, and Developer Productivity
13 May 2024, Embedded Computing Design

McObject LLC Joins STMicroelectronics Partner Program to Expand, Enhance and Accelerate Customer
6 June 2024, EIN News

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

McObject Announces the Release of eXtremeDB/rt 1.2
23 May 2023, Embedded Computing Design

provided by Google News

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates
31 May 2024, Microsoft

Update records in a Kusto Database (public preview) | Azure updates
20 February 2024, Microsoft

Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates
8 January 2024, Microsoft

New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates
24 January 2024, Microsoft

Public Preview: Azure Data Explorer Add-On for Splunk | Azure updates
3 October 2023, Microsoft

provided by Google News

Announcing FOCUS support for OCI cost reports to make multicloud FinOps easier
6 June 2024, Oracle

Oracle Database Testing
2 June 2024, ITPro Today

Announcing Oracle Database 23ai : General Availability
2 May 2024, Oracle

Understanding the different Oracle Database options under the OCI-Microsoft Azure partnership
21 May 2024, Oracle

Oracle Database Revenue Fell in First Quarter
5 June 2024, ITPro Today

provided by Google News

Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose
2 February 2024, Towards Data Science

Manticore is a Faster Alternative to Elasticsearch in C++
25 July 2022, hackernoon.com

Perplexity AI: From Its Use To Operation, Everything You Need To Know About Google's Newest Challenger
11 January 2024, Free Press Journal

The Pirate Bay was recently down for over a week due to a DDoS attack
29 October 2019, The Hacker News

Beyond the Concert Hall: 5 Organizations Making a Difference in Classical Music in 2018 | WQXR Editorial
22 December 2018, WQXR Radio

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here