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DBMS > eXtremeDB vs. Hawkular Metrics vs. Microsoft Azure AI Search vs. Microsoft Azure Data Explorer vs. TimescaleDB

System Properties Comparison eXtremeDB vs. Hawkular Metrics vs. Microsoft Azure AI Search vs. Microsoft Azure Data Explorer vs. TimescaleDB

Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Search-as-a-service for web and mobile app developmentFully managed big data interactive analytics platformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSSearch engineRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsVector DBMSDocument 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.mcobject.comwww.hawkular.orgazure.microsoft.com/­en-us/­services/­searchazure.microsoft.com/­services/­data-explorerwww.timescale.com
Technical documentationwww.mcobject.com/­docs/­extremedb.htmwww.hawkular.org/­hawkular-metrics/­docs/­user-guidelearn.microsoft.com/­en-us/­azure/­searchdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.timescale.com
DeveloperMcObjectCommunity supported by Red HatMicrosoftMicrosoftTimescale
Initial release20012014201520192017
Current release8.2, 2021V1cloud service with continuous releases2.13.0, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++JavaC
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
hostedhostedLinux
OS X
Windows
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-typesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.no infosupport of XML interfaces availablenonoyesyes
Secondary indexesyesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infowith the option: eXtremeSQLnonoKusto Query Language (KQL), SQL subsetyes infofull PostgreSQL SQL syntax
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
HTTP RESTRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
Go
Java
Python
Ruby
C#
Java
JavaScript
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnonoYes, possible languages: KQL, Python, Ruser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes infoby defining eventsyes infovia Hawkular Alertingnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud serviceyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
selectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyesyes
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 controlnoyes infousing Azure authenticationAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
eXtremeDBHawkular MetricsMicrosoft Azure AI SearchMicrosoft Azure Data ExplorerTimescaleDB
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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eXtremeDBHawkular MetricsMicrosoft Azure AI SearchMicrosoft Azure Data ExplorerTimescaleDB
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