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DBMS > Atos Standard Common Repository vs. HBase vs. Solr vs. Sqrrl

System Properties Comparison Atos Standard Common Repository vs. HBase vs. Solr vs. Sqrrl

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonHBase  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksWide-column store based on Apache Hadoop and on concepts of BigTableA widely used distributed, scalable search engine based on Apache LuceneAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument store
Key-value store
Wide column storeSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score31.25
Rank#26  Overall
#2  Wide column stores
Score44.28
Rank#24  Overall
#3  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryhbase.apache.orgsolr.apache.orgsqrrl.com
Technical documentationhbase.apache.org/­book.htmlsolr.apache.org/­resources.html
DeveloperAtos Convergence CreatorsApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release2016200820062012
Current release17032.3.4, January 20219.5.0, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJavaJava
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
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-free, schema definition possibleyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateoptionaloptions to bring your own types, AVROyes 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.yesnoyes
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnonoSolr Parallel SQL Interfaceno
APIs and other access methodsLDAPJava API
RESTful HTTP API
Thrift
Java API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesAll languages with LDAP bindingsC
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyes infoCoprocessors in JavaJava pluginsno
Triggersyesyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
yesselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsSingle row ACID (across millions of columns)optimistic lockingAtomic updates per row, document, or graph entity
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.yesyesyes
User concepts infoAccess controlLDAP bind authenticationAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Atos Standard Common RepositoryHBaseSolrSqrrl
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