DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > 4D vs. Atos Standard Common Repository vs. Datastax Enterprise vs. Microsoft Azure Data Explorer

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Datastax Enterprise vs. Microsoft Azure Data Explorer

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionApplication development environment with integrated database management systemHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Fully managed big data interactive analytics platform
Primary database modelRelational DBMSDocument store
Key-value store
Wide column storeRelational DBMS infocolumn oriented
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score5.80
Rank#60  Overall
#4  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.4d.comatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.datastax.com/­products/­datastax-enterpriseazure.microsoft.com/­services/­data-explorer
Technical documentationdeveloper.4d.comdocs.datastax.comdocs.microsoft.com/­en-us/­azure/­data-explorer
Developer4D, IncAtos Convergence CreatorsDataStaxMicrosoft
Initial release1984201620112019
Current releasev20, April 202317036.8, April 2020cloud service with continuous releases
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaJava
Server operating systemsOS X
Windows
LinuxLinux
OS X
hosted
Data schemeyesSchema and schema-less with LDAP viewsschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesoptionalyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.yesyesnoyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLyes infoclose to SQL 92noSQL-like DML and DDL statements (CQL); Spark SQLKusto Query Language (KQL), SQL subset
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
LDAPProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages4D proprietary IDE
PHP
All languages with LDAP bindingsC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnonoYes, possible languages: KQL, Python, R
Triggersyesyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionSharding infono "single point of failure"Sharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesconfigurable replication factor, datacenter aware, advanced replication for edge computingyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsno infoAtomicity and isolation are supported for single operationsno
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.noyesyesno
User concepts infoAccess controlUsers and groupsLDAP bind authenticationAccess rights for users can be defined per objectAzure Active Directory Authentication
More information provided by the system vendor
4D infoformer name: 4th DimensionAtos Standard Common RepositoryDatastax EnterpriseMicrosoft Azure Data Explorer
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» 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
4D infoformer name: 4th DimensionAtos Standard Common RepositoryDatastax EnterpriseMicrosoft Azure Data Explorer
DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

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

provided by Google News

DataStax and LlamaIndex Partner to Make Building RAG Applications Easier than Ever for GenAI Developers
20 February 2024, businesswire.com

DataStax Introduces Enhanced RAG Capabilities Through Astra DB and NVIDIA Tech
19 March 2024, Datanami

DataStax Rolls Out Vector Search for Astra DB to Support Gen AI
19 July 2023, EnterpriseAI

DataStax adds vector search to boost support for generative AI workloads
18 July 2023, SiliconANGLE News

DataStax goes vector searching with Astra DB – Blocks and Files
20 July 2023, Blocks & Files

provided by Google News

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Introducing Microsoft Fabric: The data platform for the era of AI | Microsoft Azure Blog
23 May 2023, Microsoft

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, microsoft.com

Azure Data Explorer and Stream Analytics for anomaly detection
16 January 2020, Microsoft

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, Microsoft

provided by Google News



Share this page

Featured Products

SingleStore logo

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

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

RaimaDB logo

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

Milvus logo

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

Present your product here