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DBMS > FeatureBase vs. Hawkular Metrics vs. HEAVY.AI

System Properties Comparison FeatureBase vs. Hawkular Metrics vs. HEAVY.AI

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#293  Overall
#134  Relational DBMS
Score0.07
Rank#366  Overall
#38  Time Series DBMS
Score2.30
Rank#127  Overall
#60  Relational DBMS
Websitewww.featurebase.comwww.hawkular.orggithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdocs.featurebase.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.heavy.ai
DeveloperMolecula and Pilosa Open Source ContributorsCommunity supported by Red HatHEAVY.AI, Inc.
Initial release201720142016
Current release2022, May 20225.10, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC++ and CUDA
Server operating systemsLinux
macOS
Linux
OS X
Windows
Linux
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesnonono
SQL infoSupport of SQLSQL queriesnoyes
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
HTTP RESTJDBC
ODBC
Thrift
Vega
Supported programming languagesJava
Python
Go
Java
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresnono
Triggersnoyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on CassandraMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standard

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More resources
FeatureBaseHawkular MetricsHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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