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

DBMS > AlaSQL vs. Apache Druid vs. HEAVY.AI vs. Microsoft Azure Data Explorer

System Properties Comparison AlaSQL vs. Apache Druid vs. HEAVY.AI vs. Microsoft Azure Data Explorer

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonApache Druid  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionJavaScript DBMS libraryOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platform
Primary database modelDocument store
Relational DBMS
Relational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMSDocument 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
Score0.51
Rank#256  Overall
#40  Document stores
#118  Relational DBMS
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitealasql.orgdruid.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorer
Technical documentationgithub.com/­AlaSQL/­alasqldruid.apache.org/­docs/­latest/­designdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAndrey Gershun & Mathias R. WulffApache Software Foundation and contributorsHEAVY.AI, Inc.Microsoft
Initial release2014201220162019
Current release29.0.1, April 20245.10, January 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoMIT-LicenseOpen Source infoApache license v2Open Source infoApache Version 2; enterprise edition availablecommercial
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.
Implementation languageJavaScriptJavaC++ and CUDA
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Unix
Linuxhosted
Data schemeschema-freeyes infoschema-less columns are supportedyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datenoyesyesyes 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.nononoyes
Secondary indexesnoyesnoall fields are automatically indexed
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.SQL for queryingyesKusto Query Language (KQL), SQL subset
APIs and other access methodsJavaScript APIJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJavaScriptClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnononoYes, possible languages: KQL, Python, R
Triggersyesnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedSharding infoRound robinSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, via HDFS, S3 or other storage enginesMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storagenonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlnoRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAzure Active Directory Authentication

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
AlaSQLApache DruidHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data Explorer
Recent citations in the news

Create a Marvel Database with SQL and Javascript, the easy way
2 July 2019, Towards Data Science

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards
26 January 2024, Datanami

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

How to connect DataGrip to Apache Druid | by Zisis Flokas
18 October 2021, Towards Data Science

provided by Google News

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

Making the most of geospatial intelligence
14 April 2023, InfoWorld

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

provided by Google 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

Migration of Azure Virtual Network injected Azure Data Explorer cluster to Private Endpoints | Azure updates
4 December 2023, Microsoft

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.

Milvus logo

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