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DBMS > FatDB vs. Hawkular Metrics vs. Spark SQL vs. TimescaleDB

System Properties Comparison FatDB vs. Hawkular Metrics vs. Spark SQL vs. TimescaleDB

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Spark SQL is a component on top of 'Spark Core' for structured data processingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#355  Overall
#31  Time Series DBMS
Score23.04
Rank#35  Overall
#21  Relational DBMS
Score4.52
Rank#83  Overall
#5  Time Series DBMS
Websitewww.hawkular.orgspark.apache.org/­sqlwww.timescale.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperFatCloudCommunity supported by Red HatApache Software FoundationTimescale
Initial release2012201420142017
Current release3.3.0, June 20222.6.0, February 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaScalaC
Server operating systemsWindowsLinux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, 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.nonoyes
Secondary indexesyesnonoyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HTTP RESTJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#Go
Java
Python
Ruby
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infovia applicationsnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes infovia applicationsyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrayes, utilizing Spark Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infobased on CassandranoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsnonofine grained access rights according to SQL-standard
More information provided by the system vendor
FatDBHawkular MetricsSpark SQLTimescaleDB
Specific characteristicsTimescale is the creator of TimescaleDB , the first open-source relational database...
» more
Competitive advantagesTimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more
Typical application scenariosTime-series Analytics TimescaleDB boosts the performance of PostgreSQL for time-series...
» more
Key customersTransferWise, Maersk, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco, Nutanix, Warner...
» more
Market metricsWith over 12,700 GitHub stars and growing, 1,000,000 active databases, and an active...
» more
Licensing and pricing modelsTimescaleDB is available as a self-hosted product under two licenses, the Timescale...
» more

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3rd partiesSQLFlow: Provides a visual representation of the overall flow of data. Automated SQL data lineage analysis across Databases, ETL, Business Intelligence, Cloud and Hadoop environments by parsing SQL Script and stored procedure.
» more

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More resources
FatDBHawkular MetricsSpark SQLTimescaleDB
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