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

DBMS > Heroic vs. InterSystems Caché vs. LeanXcale vs. Lovefield vs. Microsoft Azure Data Explorer

System Properties Comparison Heroic vs. InterSystems Caché vs. LeanXcale vs. Lovefield vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonLeanXcale  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA multi-model DBMS and application serverA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesEmbeddable relational database for web apps written in pure JavaScriptFully managed big data interactive analytics platform
Primary database modelTime Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Key-value store
Relational DBMS
Relational DBMSRelational 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
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitegithub.com/­spotify/­heroicwww.intersystems.com/­products/­cachewww.leanxcale.comgoogle.github.io/­lovefieldazure.microsoft.com/­services/­data-explorer
Technical documentationspotify.github.io/­heroicdocs.intersystems.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperSpotifyInterSystemsLeanXcaleGoogleMicrosoft
Initial release20141997201520142019
Current release2018.1.4, May 20202.1.12, February 2017cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0commercial
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 languageJavaJavaScript
Server operating systemsAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safarihosted
Data schemeschema-freedepending on used data modelyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes 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.noyesnoyes
Secondary indexesyes infovia Elasticsearchyesyesall fields are automatically indexed
SQL infoSupport of SQLnoyesyes infothrough Apache DerbySQL-like query language infovia JavaScript builder patternKusto Query Language (KQL), SQL subset
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
C++
Java
C
Java
Scala
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyesnoYes, possible languages: KQL, Python, R
TriggersnoyesUsing read-only observersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnoneyes 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 systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infousing MemoryDBno
User concepts infoAccess controlAccess rights for users, groups and rolesnoAzure 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
HeroicInterSystems CachéLeanXcaleLovefieldMicrosoft Azure Data Explorer
Recent citations in the news

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

provided by Google News

AWS, GCP, Oracle, Azure, SAP Lead Cloud DBMS Market: Gartner
12 February 2022, CRN

Epic On EHR Interoperability: Not A '1-Time Project'
10 April 2015, InformationWeek

Associative Data Modeling Demystified - Part1 - DataScienceCentral.com
9 July 2016, Data Science Central

Announcing IBM Spectrum Sentinel: Building a Cyber Resilient Future
24 June 2022, IBM

Choosing a Database Technology. A roadmap and process overview | by Shirish Joshi
23 February 2020, Towards Data Science

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

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

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here