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

DBMS > Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer vs. Splice Machine vs. Tigris

System Properties Comparison Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer vs. Splice Machine vs. Tigris

Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSplice Machine  Xexclude from comparisonTigris  Xexclude from comparison
DescriptionTime 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 platformOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMSDocument store
Key-value store
Search engine
Time Series 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
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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Websitegithub.com/­spotify/­heroicwww.leanxcale.comazure.microsoft.com/­services/­data-explorersplicemachine.comwww.tigrisdata.com
Technical documentationspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorersplicemachine.com/­how-it-workswww.tigrisdata.com/­docs
DeveloperSpotifyLeanXcaleMicrosoftSplice MachineTigris Data, Inc.
Initial release20142015201920142022
Current releasecloud service with continuous releases3.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.noyesno
Secondary indexesyes infovia Elasticsearchall fields are automatically indexedyesyes
SQL infoSupport of SQLnoyes infothrough Apache DerbyKusto Query Language (KQL), SQL subsetyesno
APIs and other access methodsHQL (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
JDBC
Native Spark Datasource
ODBC
CLI Client
gRPC
RESTful HTTP API
Supported programming languagesC
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Ryes infoJavano
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardAccess rights for 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
HeroicLeanXcaleMicrosoft Azure Data ExplorerSplice MachineTigris
Recent citations in the 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

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Splice Machine scores $15M to make Hadoop run in real time
10 February 2014, VentureBeat

provided by Google News

Tigris Data Unveils Beta Launch of New Vector Search Tool
19 May 2023, Datanami

Tigris Data Launches All-in-One Developer Data Platform
27 September 2022, Datanami

FerretDB Provides Alternative to MongoDB
19 May 2023, Datanami

Latest Asigra platform targets SaaS backup for MSPs
6 March 2023, TechTarget

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