DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Microsoft Azure Table Storage vs. OpenMLDB vs. Tarantool

System Properties Comparison Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Microsoft Azure Table Storage vs. OpenMLDB vs. Tarantool

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOpenMLDB  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformDatabase as a Service offering with high compatibility to Microsoft SQL ServerA Wide Column Store for rapid development using massive semi-structured datasetsAn open-source machine learning database that provides a feature platform for training and inferenceIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMS infocolumn orientedRelational DBMSWide column storeTime Series DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument 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
Document store
Graph DBMS
Spatial DBMS
Relational DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.10
Rank#359  Overall
#36  Time Series DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­products/­azure-sql/­databaseazure.microsoft.com/­en-us/­services/­storage/­tablesopenmldb.aiwww.tarantool.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­en-us/­azure/­azure-sqlopenmldb.ai/­docs/­zh/­mainwww.tarantool.io/­en/­doc
DeveloperMicrosoftMicrosoftMicrosoft4 Paradigm Inc.VK
Initial release20192010201220202008
Current releasecloud service with continuous releasesV122024-2 February 20242.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen SourceOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, Java, ScalaC and C++
Server operating systemshostedhostedhostedLinuxBSD
Linux
macOS
Data schemeFixed schema with schema-less datatypes (dynamic)yesschema-freeFixed schemaFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.yesyesnonono
Secondary indexesall fields are automatically indexedyesnoyesyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyesnoyesFull-featured ANSI SQL support
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
SQLAlchemy
Open binary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
Python
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RTransact SQLnonoLua, C and SQL stored procedures
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with always 3 replicas availableyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAzure Active Directory Authenticationfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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
Microsoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureMicrosoft Azure Table StorageOpenMLDBTarantool
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

show all

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

show all

Recent citations in the news

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates
31 May 2024, Microsoft

Update records in a Kusto Database (public preview) | Azure updates
20 February 2024, Microsoft

Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates
8 January 2024, Microsoft

Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ...
5 February 2024, Microsoft

New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates
24 January 2024, Microsoft

provided by Google News

Copilot in Azure SQL Database in Private Preview
27 March 2024, InfoQ.com

Microsoft unveils Copilot for Azure SQL Database
27 March 2024, InfoWorld

Azure SQL Database migration to OCI - resources estimation and migration approach
11 January 2024, Oracle

Public Preview: New Azure SQL Database skills introduced to Microsoft Copilot in Azure | Azure updates
21 May 2024, Microsoft

Azure SQL Database outage caused by network infrastructure
18 September 2023, The Register

provided by Google News

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

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

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

Inside Azure File Storage
7 October 2015, azure.microsoft.com

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

provided by Google News

MLOp practice: using OpenMLDB in the real-time anti-fraud model for the bank's online transaction
23 August 2021, Towards Data Science

Predictive maintenance — 5minutes demo of an end to end machine learning project
13 August 2021, Towards Data Science

provided by Google News

Deploying Tarantool Cartridge applications with zero effort (Part 1)
16 December 2019, Хабр

VShard — horizontal scaling in Tarantool
7 March 2019, Хабр

Accelerating PHP connectors for Tarantool using Async, Swoole, and Parallel
18 December 2019, Хабр

provided by Google News



Share this page

Featured Products

Milvus logo

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

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

Present your product here