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DBMS > Atos Standard Common Repository vs. Databricks vs. GridGain vs. Machbase Neo vs. Sphinx

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. GridGain vs. Machbase Neo vs. Sphinx

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonSphinx  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.GridGain is an in-memory computing platform, built on Apache IgniteTimeSeries DBMS for AIoT and BigDataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Columnar
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score0.07
Rank#348  Overall
#34  Time Series DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comwww.gridgain.commachbase.comsphinxsearch.com
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmlmachbase.com/­dbmssphinxsearch.com/­docs
DeveloperAtos Convergence CreatorsDatabricksGridGain Systems, Inc.MachbaseSphinx Technologies Inc.
Initial release20162013200720132001
Current release1703GridGain 8.5.1V8.0, August 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial, open sourcecommercial infofree test version availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .Net, Python, REST, SQLCC++
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
z/OS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateoptionalyesyesno
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.yesyesyesno
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnowith Databricks SQLANSI-99 for query and DML statements, subset of DDLSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Proprietary protocol
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)nono
Triggersyesyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes (replicated cache)selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes infovolatile and lookup table
User concepts infoAccess controlLDAP bind authenticationRole-based access control
Security Hooks for custom implementations
simple password-based access controlno
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksGridGainMachbase Neo infoFormer name was InfinifluxSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Atos Standard Common RepositoryDatabricksGridGainMachbase Neo infoFormer name was InfinifluxSphinx
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