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DBMS > Hawkular Metrics vs. Microsoft Azure Synapse Analytics vs. TimescaleDB vs. Vitess

System Properties Comparison Hawkular Metrics vs. Microsoft Azure Synapse Analytics vs. TimescaleDB vs. Vitess

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.hawkular.orgazure.microsoft.com/­services/­synapse-analyticswww.timescale.comvitess.io
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­azure/­synapse-analyticsdocs.timescale.comvitess.io/­docs
DeveloperCommunity supported by Red HatMicrosoftTimescaleThe Linux Foundation, PlanetScale
Initial release2014201620172013
Current release2.13.0, November 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++CGo
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Windows
Docker
Linux
macOS
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex 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.nonoyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyesyes infofull PostgreSQL SQL syntaxyes infowith proprietary extensions
APIs and other access methodsHTTP RESTADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesGo
Java
Python
Ruby
C#
Java
PHP
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
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 proceduresnoTransact SQLuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes infoproprietary syntax
Triggersyes infovia Hawkular Alertingnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding, horizontal partitioningyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandrayesSource-replica replication with hot standby and reads on replicas infoMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoyesfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
Hawkular MetricsMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTimescaleDBVitess
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