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DBMS > Badger vs. Hawkular Metrics vs. HEAVY.AI vs. Spark SQL

System Properties Comparison Badger vs. Hawkular Metrics vs. HEAVY.AI vs. Spark SQL

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.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 hardwareSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.hawkular.orggithub.com/­heavyai/­heavydb
www.heavy.ai
spark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.heavy.aispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsCommunity supported by Red HatHEAVY.AI, Inc.Apache Software Foundation
Initial release2017201420162014
Current release5.10, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaC++ and CUDAScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nononono
Secondary indexesnononono
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsHTTP RESTJDBC
ODBC
Thrift
Vega
JDBC
ODBC
Supported programming languagesGoGo
Java
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersnoyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on CassandraSharding infoRound robinyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infobased on CassandraMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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.nonoyesno
User concepts infoAccess controlnonofine grained access rights according to SQL-standardno

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BadgerHawkular MetricsHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Spark SQL
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