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

DBMS > Cachelot.io vs. Dolt vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer

System Properties Comparison Cachelot.io vs. Dolt vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonDolt  Xexclude from comparisonHeroic  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionIn-memory caching systemA MySQL compatible DBMS with Git-like versioning of data and schemaTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platform
Primary database modelKey-value storeRelational DBMSTime Series DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument storeDocument 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
Score0.04
Rank#388  Overall
#62  Key-value stores
Score1.02
Rank#191  Overall
#89  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitecachelot.iogithub.com/­dolthub/­dolt
www.dolthub.com
github.com/­spotify/­heroicwww.leanxcale.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.dolthub.comspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDoltHub IncSpotifyLeanXcaleMicrosoft
Initial release20152018201420152019
Current releasecloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicenseOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoJava
Server operating systemsFreeBSD
Linux
OS X
Linux
macOS
Windows
hosted
Data schemeschema-freeyesschema-freeyesFixed 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 indexesnoyesyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLnoyesnoyes infothrough Apache DerbyKusto Query Language (KQL), SQL subset
APIs and other access methodsMemcached protocolCLI Client
HTTP REST
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes infocurrently in alpha releasenoYes, possible languages: KQL, Python, R
Triggersnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentnoyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnoOnly one user is configurable, and must be specified in the config file at startupAzure 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
Cachelot.ioDoltHeroicLeanXcaleMicrosoft Azure Data Explorer
Recent citations in the news

Dolt- A Version Controlled Database
29 January 2024, iProgrammer

Top Data Version Control Tools for Machine Learning Research in 2023
24 July 2023, MarkTechPost

Dolt, a Relational Database with Git-Like Cloning Features
19 August 2020, The New Stack

Data Versioning at Scale: Chaos and Chaos Management
10 February 2023, InfoQ.com

25 Hot New Data Tools and What They DON'T Do
14 May 2020, Towards Data Science

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

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)
20 February 2024, Microsoft

Public Preview: Azure Data Explorer connector for Apache Flink
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



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