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DBMS > Atos Standard Common Repository vs. Databricks vs. Google Cloud Spanner vs. RavenDB vs. TigerGraph

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. Google Cloud Spanner vs. RavenDB vs. TigerGraph

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonRavenDB  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.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Open Source Operational and Transactional Enterprise NoSQL Document DatabaseA 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
Relational DBMSDocument storeGraph DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comcloud.google.com/­spannerravendb.netwww.tigergraph.com
Technical documentationdocs.databricks.comcloud.google.com/­spanner/­docsravendb.net/­docsdocs.tigergraph.com
DeveloperAtos Convergence CreatorsDatabricksGoogleHibernating Rhinos
Initial release20162013201720102017
Current release17035.4, July 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPL version 3, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#C++
Server operating systemsLinuxhostedhostedLinux
macOS
Raspberry Pi
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesnoyes
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.yesyesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnowith Databricks SQLyes infoQuery statements complying to ANSI 2011SQL-like query language (RQL)SQL-like query language (GSQL)
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
Go
Java
JavaScript (Node.js)
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoyesyes
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication with 3 replicas for regional instances.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACID infoStrict serializable isolationACID, Cluster-wide transaction availableACID
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.yesnonono
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Authorization levels configured per client per databaseRole-based access control
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksGoogle Cloud SpannerRavenDBTigerGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Atos Standard Common RepositoryDatabricksGoogle Cloud SpannerRavenDBTigerGraph
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