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DBMS > Atos Standard Common Repository vs. Databricks vs. Fauna vs. Google Cloud Datastore

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. Fauna vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGoogle Cloud Datastore  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.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score1.55
Rank#143  Overall
#26  Document stores
#13  Graph DBMS
#66  Relational DBMS
#13  Time Series DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comfauna.comcloud.google.com/­datastore
Technical documentationdocs.databricks.comdocs.fauna.comcloud.google.com/­datastore/­docs
DeveloperAtos Convergence CreatorsDatabricksFauna, Inc.Google
Initial release2016201320142008
Current release1703
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScala
Server operating systemsLinuxhostedhostedhosted
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateoptionalnoyes, details here
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 SQLnoSQL-like query language (GQL)
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions and aggregatesuser defined functionsusing Google App Engine
TriggersyesnoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionhorizontal partitioning infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replicationMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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.yesnonono
User concepts infoAccess controlLDAP bind authenticationIdentity management, authentication, and access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksFauna infopreviously named FaunaDBGoogle Cloud Datastore
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Atos Standard Common RepositoryDatabricksFauna infopreviously named FaunaDBGoogle Cloud Datastore
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