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DBMS > HEAVY.AI vs. SingleStore vs. Trafodion

System Properties Comparison HEAVY.AI vs. SingleStore vs. Trafodion

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#162  Overall
#73  Relational DBMS
Score3.90
Rank#69  Overall
#37  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.singlestore.comtrafodion.apache.org
Technical documentationdocs.heavy.aidocs.singlestore.comtrafodion.apache.org/­documentation.html
DeveloperHEAVY.AI, Inc.SingleStore Inc.Apache Software Foundation, originally developed by HP
Initial release201620132014
Current release5.10, January 20228.5, January 20242.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercial infofree developer edition availableOpen 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++, GoC++, Java
Server operating systemsLinuxLinux info64 bit version requiredLinux
Data schemeyesyesyes
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 indexesnoyesyes
SQL infoSupport of SQLyesyes infobut no triggers and foreign keysyes
APIs and other access methodsJDBC
ODBC
Thrift
Vega
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
Bash
C
C#
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoyesJava Stored Procedures
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infohash partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replication infostores two copies of each physical data partition on two separate nodesyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infocan define user-defined aggregate functions for map-reduce-style calculationsyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardFine grained access control via users, groups and rolesfine grained access rights according to SQL-standard

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022SingleStore infoformer name was MemSQLTrafodion
DB-Engines blog posts

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022,  Akmal Chaudhri, SingleStore (sponsor) 

Cloud-Based Analytics With SingleStoreDB
9 June 2022,  Akmal Chaudhri, SingleStore (sponsor) 

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022,  Akmal Chaudhri, SingleStore (sponsor) 

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Recent citations in the news

5 Q’s for Mike Flaxman, Vice President of Heavy.AI
15 August 2024, Center for Data Innovation

HEAVY.AI Accelerates Big Data Analytics with Vultr's High-Performance GPU Cloud Infrastructure
11 September 2024, insideBIGDATA

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

Making the most of geospatial intelligence
14 April 2023, InfoWorld

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

provided by Google News

Third time was the charm for SingleStore in the cloud, CEO says
8 July 2024, The Register

SingleStore Acquires BryteFlow ​​to Accelerate Adoption of Real-Time Analytics, GenAI
3 October 2024, Business Wire

SingleStore acquires BryteFlow to boost data ingestion capabilities
3 October 2024, InfoWorld

SingleStore acquires BryteFlow to better digest ERP and CRM data
4 October 2024, Blocks and Files

SingleStore's BryteFlow acquisition targets data integration
3 October 2024, TechTarget

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News



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