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DBMS > Badger vs. HEAVY.AI vs. Rockset vs. Spark SQL

System Properties Comparison Badger vs. HEAVY.AI vs. Rockset vs. Spark SQL

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMSRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgergithub.com/­heavyai/­heavydb
www.heavy.ai
rockset.comspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.heavy.aidocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsHEAVY.AI, Inc.RocksetApache Software Foundation
Initial release2017201620192014
Current release5.10, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++ and CUDAC++Scala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxhostedLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesdynamic typingyes
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 infoingestion from XML files supportedno
Secondary indexesnonoall fields are automatically indexedno
SQL infoSupport of SQLnoyesRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
Vega
HTTP RESTJDBC
ODBC
Supported programming languagesGoAll languages supporting JDBC/ODBC/Thrift
Python
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoRound robinAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual 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.noyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
BadgerHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022RocksetSpark SQL
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