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DBMS > Atos Standard Common Repository vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Titan vs. Vitess

System Properties Comparison Atos Standard Common Repository vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Titan vs. Vitess

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTitan  Xexclude from comparisonVitess  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerTitan is a Graph DBMS optimized for distributed clusters.Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSGraph DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­spotify/­heroicazure.microsoft.com/­services/­synapse-analyticsgithub.com/­thinkaurelius/­titanvitess.io
Technical documentationspotify.github.io/­heroicdocs.microsoft.com/­azure/­synapse-analyticsgithub.com/­thinkaurelius/­titan/­wikivitess.io/­docs
DeveloperAtos Convergence CreatorsSpotifyMicrosoftAurelius, owned by DataStaxThe Linux Foundation, PlanetScale
Initial release20162014201620122013
Current release170315.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache license, version 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++JavaGo
Server operating systemsLinuxhostedLinux
OS X
Unix
Windows
Docker
Linux
macOS
Data schemeSchema and schema-less with LDAP viewsschema-freeyesyesyes
Typing infopredefined data types such as float or dateoptionalyesyesyesyes
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.yesnono
Secondary indexesyesyes infovia Elasticsearchyesyesyes
SQL infoSupport of SQLnonoyesnoyes infowith proprietary extensions
APIs and other access methodsLDAPHQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
ODBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages with LDAP bindingsC#
Java
PHP
Clojure
Java
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoTransact SQLyesyes infoproprietary syntax
Triggersyesnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding, horizontal partitioningyes infovia pluggable storage backendsSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes infoRelationships in graphyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlLDAP bind authenticationyesUser authentification and security via Rexster Graph ServerUsers with fine-grained authorization concept infono user groups or roles

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More resources
Atos Standard Common RepositoryHeroicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTitanVitess
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