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DBMS > Atos Standard Common Repository vs. HEAVY.AI vs. Kinetica vs. Solr vs. Teradata Aster

System Properties Comparison Atos Standard Common Repository vs. HEAVY.AI vs. Kinetica vs. Solr vs. Teradata Aster

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparisonTeradata Aster  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsA widely used distributed, scalable search engine based on Apache LucenePlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comsolr.apache.org
Technical documentationdocs.heavy.aidocs.kinetica.comsolr.apache.org/­resources.html
DeveloperAtos Convergence CreatorsHEAVY.AI, Inc.KineticaApache Software FoundationTeradata
Initial release20162016201220062005
Current release17035.10, January 20227.1, August 20219.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ and CUDAC, C++Java
Server operating systemsLinuxLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeSchema and schema-less with LDAP viewsyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateoptionalyesyesyes infosupports customizable data types and automatic 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.yesnonoyesyes infoin Aster File Store
Secondary indexesyesnoyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSolr Parallel SQL Interfaceyes
APIs and other access methodsLDAPJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages with LDAP bindingsAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonouser defined functionsJava pluginsR packages
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding infoRound robinShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationSource-replica replicationyesyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlLDAP bind authenticationfine grained access rights according to SQL-standardAccess rights for users and roles on table levelyesfine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaSolrTeradata Aster
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