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DBMS > Atos Standard Common Repository vs. Databricks vs. etcd vs. Google Cloud Spanner vs. Microsoft Azure AI Search

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. etcd vs. Google Cloud Spanner vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft Azure AI Search  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 distributed reliable key-value storeA 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.Search-as-a-service for web and mobile app development
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Key-value storeRelational DBMSSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.cometcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­spannerazure.microsoft.com/­en-us/­services/­search
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­spanner/­docslearn.microsoft.com/­en-us/­azure/­search
DeveloperAtos Convergence CreatorsDatabricksGoogleMicrosoft
Initial release2016201320172015
Current release17033.4, August 2019V1
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemsLinuxhostedFreeBSD
Linux
Windows infoexperimental
hostedhosted
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateoptionalnoyesyes
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.yesyesnonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnowith Databricks SQLnoyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnonono
Triggersyesyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication with 3 replicas for regional instances.yes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnoACID infoStrict serializable isolationno
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.yesnononono
User concepts infoAccess controlLDAP bind authenticationnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing Azure authentication
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksetcdGoogle Cloud SpannerMicrosoft Azure AI Search
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Atos Standard Common RepositoryDatabricksetcdGoogle Cloud SpannerMicrosoft Azure AI Search
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