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. Hawkular Metrics vs. Microsoft Azure Table Storage vs. TypeDB

System Properties Comparison Atos Standard Common Repository vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. TypeDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTypeDB infoformerly named Grakn  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 networksHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A Wide Column Store for rapid development using massive semi-structured datasetsTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelDocument store
Key-value store
Time Series DBMSWide column storeGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.65
Rank#234  Overall
#20  Graph DBMS
#107  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.hawkular.orgazure.microsoft.com/­en-us/­services/­storage/­tablestypedb.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidetypedb.com/­docs
DeveloperAtos Convergence CreatorsCommunity supported by Red HatMicrosoftVaticle
Initial release2016201420122016
Current release17032.26.3, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesyesyes
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.yesnonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLnononono
APIs and other access methodsLDAPHTTP RESTRESTful HTTP APIgRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languagesAll languages with LDAP bindingsGo
Java
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnononono
Triggersyesyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandrayes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnooptimistic lockingACID
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 authenticationnoAccess rights based on private key authentication or shared access signaturesyes infoat REST API level; other APIs in progress
More information provided by the system vendor
Atos Standard Common RepositoryHawkular MetricsMicrosoft Azure Table StorageTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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 RepositoryHawkular MetricsMicrosoft Azure Table StorageTypeDB infoformerly named Grakn
Recent citations in the news

Infographic: What makes a Mobile Operator's setup future proof?
10 February 2024, Atos

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

Azure Cosmos DB Data Migration tool imports from Azure Table storage | Azure updates
5 May 2015, Microsoft

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

provided by Google News

An Enterprise Data Stack Using TypeDB | by Daniel Crowe
2 September 2021, Towards Data Science

Spacecraft Engineering Models: How to Migrate UML to TypeQL
8 September 2021, hackernoon.com

Speedb Goes Open Source With Its Speedb Data Engine, A Drop-in Replacement for RocksDB
9 November 2022, Business Wire

195 Data Science Libraries You Should Reconsider Using | by Dimitris Effrosynidis
2 February 2024, DataDrivenInvestor

Modelling Biomedical Data for a Drug Discovery Knowledge Graph
6 October 2020, Towards Data Science

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

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

SingleStore logo

Database for your real-time AI and Analytics Apps.
Try it today.

Present your product here