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DBMS > Atos Standard Common Repository vs. Databricks vs. GigaSpaces vs. Heroic vs. TigerGraph

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. GigaSpaces vs. Heroic vs. TigerGraph

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHeroic  Xexclude from comparisonTigerGraph  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 networksThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSGraph DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comwww.gigaspaces.comgithub.com/­spotify/­heroicwww.tigergraph.com
Technical documentationdocs.databricks.comdocs.gigaspaces.com/­latest/­landing.htmlspotify.github.io/­heroicdocs.tigergraph.com
DeveloperAtos Convergence CreatorsDatabricksGigaspaces TechnologiesSpotify
Initial release20162013200020142017
Current release170315.5, September 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetJavaC++
Server operating systemsLinuxhostedLinux
macOS
Solaris
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesyesyes
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.yesyesno infoXML can be used for describing objects metadatanono
Secondary indexesyesyesyesyes infovia Elasticsearch
SQL infoSupport of SQLnowith Databricks SQLSQL-99 for query and DML statementsnoSQL-like query language (GSQL)
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HQL (Heroic Query Language, a JSON-based language)
HTTP API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
.Net
C++
Java
Python
Scala
C++
Java
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyesnoyes
Triggersyesyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDnoACID
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.yesnoyesnono
User concepts infoAccess controlLDAP bind authenticationRole-based access controlRole-based access control
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksGigaSpacesHeroicTigerGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Atos Standard Common RepositoryDatabricksGigaSpacesHeroicTigerGraph
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