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DBMS > Atos Standard Common Repository vs. GigaSpaces vs. Interbase vs. Solr vs. Vertica

System Properties Comparison Atos Standard Common Repository vs. GigaSpaces vs. Interbase vs. Solr vs. Vertica

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGigaSpaces  Xexclude from comparisonInterbase  Xexclude from comparisonSolr  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsLight-weight proven RDBMS infooriginally from BorlandA widely used distributed, scalable search engine based on Apache LuceneCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsGraph DBMS
Search engine
Spatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.gigaspaces.comwww.embarcadero.com/­products/­interbasesolr.apache.orgwww.vertica.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.embarcadero.com/­products/­interbasesolr.apache.org/­resources.htmlvertica.com/­documentation
DeveloperAtos Convergence CreatorsGigaspaces TechnologiesEmbarcaderoApache Software FoundationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20162000198420062005
Current release170315.5, September 2020InterBase 2020, December 20199.6.1, May 202412.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoApache Version 2commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetCJavaC++
Server operating systemsLinuxLinux
macOS
Solaris
Windows
Android
iOS
Linux
OS X
Windows
All 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 viewsschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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.yesno infoXML can be used for describing objects metadatano infoexport as XML data possibleyesno
Secondary indexesyesyesyesyes infoAll search fields are automatically indexedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-99 for query and DML statementsyesSolr Parallel SQL InterfaceFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsLDAPGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages with LDAP bindings.Net
C++
Java
Python
Scala
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesyes infoInterbase procedure and trigger languageJava pluginsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes, event driven architectureyesyes infoUser configurable commands triggered on index changesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnoneShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Interbase Change ViewsyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMultiversion concurreny controlyesyes
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.yesyesyesyesno
User concepts infoAccess controlLDAP bind authenticationRole-based access controlfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Atos Standard Common RepositoryGigaSpacesInterbaseSolrVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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Atos Standard Common RepositoryGigaSpacesInterbaseSolrVertica infoOpenText™ Vertica™
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