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

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

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonBadger  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.An 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 hardwareSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iogithub.com/­dgraph-io/­badgergithub.com/­heavyai/­heavydb
www.heavy.ai
spark.apache.org/­sql
Technical documentationdocs.atoti.iogodoc.org/­github.com/­dgraph-io/­badgerdocs.heavy.aispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamDGraph LabsHEAVY.AI, Inc.Apache Software Foundation
Initial release201720162014
Current release5.10, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++ and CUDAScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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 SQLMultidimensional Expressions (MDX)noyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
Vega
JDBC
ODBC
Supported programming languagesGoAll languages supporting JDBC/ODBC/Thrift
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneSharding infoRound robinyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardno

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