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DBMS > Atos Standard Common Repository vs. Databricks vs. etcd vs. Hive vs. Lovefield

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. etcd vs. Hive vs. Lovefield

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonHive  Xexclude from comparisonLovefield  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 storedata warehouse software for querying and managing large distributed datasets, built on HadoopEmbeddable relational database for web apps written in pure JavaScript
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Key-value storeRelational DBMSRelational 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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.cometcd.io
github.com/­etcd-io/­etcd
hive.apache.orggoogle.github.io/­lovefield
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cwiki.apache.org/­confluence/­display/­Hive/­Homegithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperAtos Convergence CreatorsDatabricksApache Software Foundation infoinitially developed by FacebookGoogle
Initial release2016201320122014
Current release17033.4, August 20193.1.3, April 20222.1.12, February 2017
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoApache 2.0
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 languageJavaGoJavaJavaScript
Server operating systemsLinuxhostedFreeBSD
Linux
Windows infoexperimental
All OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safari
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.yesyesnono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnowith Databricks SQLnoSQL-like DML and DDL statementsSQL-like query language infovia JavaScript builder pattern
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
JDBC
ODBC
Thrift
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
C++
Java
PHP
Python
JavaScript
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoyes infouser defined functions and integration of map-reduceno
Triggersyesyes, watching key changesnoUsing read-only observers
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Database
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infousing MemoryDB
User concepts infoAccess controlLDAP bind authenticationnoAccess rights for users, groups and rolesno
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksetcdHiveLovefield
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Atos Standard Common RepositoryDatabricksetcdHiveLovefield
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