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DBMS > HEAVY.AI vs. ReductStore vs. Spark SQL

System Properties Comparison HEAVY.AI vs. ReductStore vs. Spark SQL

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonReductStore  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­reductstore
www.reduct.store
spark.apache.org/­sql
Technical documentationdocs.heavy.aiwww.reduct.store/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHEAVY.AI, Inc.ReductStore LLCApache Software Foundation
Initial release201620232014
Current release5.10, January 20221.9, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoBusiness Source License 1.1Open Source infoApache 2.0
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 languageC++ and CUDAC++, RustScala
Server operating systemsLinuxDocker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesnono
SQL infoSupport of SQLyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
Vega
HTTP APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardno

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