DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Atos Standard Common Repository vs. Kinetica vs. ReductStore

System Properties Comparison Atos Standard Common Repository vs. Kinetica vs. ReductStore

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonKinetica  Xexclude from comparisonReductStore  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 networksFully vectorized database across both GPUs and CPUsDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.kinetica.comgithub.com/­reductstore
www.reduct.store
Technical documentationdocs.kinetica.comwww.reduct.store/­docs
DeveloperAtos Convergence CreatorsKineticaReductStore LLC
Initial release201620122023
Current release17037.1, August 20211.9, March 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++C++, Rust
Server operating systemsLinuxLinuxDocker
Linux
macOS
Windows
Data schemeSchema and schema-less with LDAP viewsyes
Typing infopredefined data types such as float or dateoptionalyes
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.yesno
Secondary indexesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statements
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
HTTP API
Supported programming languagesAll languages with LDAP bindingsC++
Java
JavaScript (Node.js)
Python
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnouser defined functions
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAM
User concepts infoAccess controlLDAP bind authenticationAccess rights for users and roles on table level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Atos Standard Common RepositoryKineticaReductStore
Recent citations in the news

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

provided by Google News



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here