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DBMS > GeoSpock vs. HEAVY.AI vs. Teradata Aster vs. Trafodion

System Properties Comparison GeoSpock vs. HEAVY.AI vs. Teradata Aster vs. Trafodion

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTrafodion  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwarePlatform for big data analytics on multistructured data sources and typesTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Websitegeospock.comgithub.com/­heavyai/­heavydb
www.heavy.ai
trafodion.apache.org
Technical documentationdocs.heavy.aitrafodion.apache.org/­documentation.html
DeveloperGeoSpockHEAVY.AI, Inc.TeradataApache Software Foundation, originally developed by HP
Initial release201620052014
Current release2.0, September 20195.10, January 20222.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptC++ and CUDAC++, Java
Server operating systemshostedLinuxLinuxLinux
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyes infoin Aster File Storeno
Secondary indexestemporal, categoricalnoyesyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)yesyesyes
APIs and other access methodsJDBCJDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Java
Python
R
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnonoR packagesJava Stored Procedures
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoSQL Map-Reduce Frameworkyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
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.noyesnono
User concepts infoAccess controlAccess rights for users can be defined per tablefine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
GeoSpockHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Teradata AsterTrafodion
Recent citations in the news

How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

Imagining an 'Everything Connected' World With Geospock | AWS Startups Blog
20 June 2019, AWS Blog

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
2 October 2020, AlexaBlockchain

Smart Cities, Autonomous Vehicles, Artificial General Intelligence Robotics: Q&A with Steve Marsh, GeoSpock
16 May 2018, ExchangeWire

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HEAVY.AI Introduces HeavyIQ, Delivering Powerful Conversational Analytics Focused on Location and Time Data
19 March 2024, Datanami

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

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

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

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Teradata Aster gets graph database, HDFS-compatible file store
8 October 2013, ZDNet

Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business
22 September 2011, PR Newswire

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

Oklahoma State grad students top winners at Teradata 2016 PARTNERS Conference
23 September 2016, Oklahoma State University

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

HP Throws Trafodion Hat into OLTP Hadoop Ring
14 July 2014, Datanami

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

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