DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > HBase vs. Microsoft Azure Data Explorer vs. Tigris vs. Vitess

System Properties Comparison HBase vs. Microsoft Azure Data Explorer vs. Tigris vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTigris  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableFully managed big data interactive analytics platformA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructureScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelWide column storeRelational DBMS infocolumn orientedDocument store
Key-value store
Search engine
Time Series DBMS
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score27.97
Rank#26  Overall
#2  Wide column stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitehbase.apache.orgazure.microsoft.com/­services/­data-explorerwww.tigrisdata.comvitess.io
Technical documentationhbase.apache.org/­book.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.tigrisdata.com/­docsvitess.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftTigris Data, Inc.The Linux Foundation, PlanetScale
Initial release2008201920222013
Current release2.3.4, January 2021cloud service with continuous releases15.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemsLinux
Unix
Windows infousing Cygwin
hostedLinux
macOS
Windows
Docker
Linux
macOS
Data schemeschema-free, schema definition possibleFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyes 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 indexesnoall fields are automatically indexedyesyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetnoyes infowith proprietary extensions
APIs and other access methodsJava API
RESTful HTTP API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
CLI Client
gRPC
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infoCoprocessors in JavaYes, possible languages: KQL, Python, Rnoyes infoproprietary syntax
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)noACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes, using FoundationDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAzure Active Directory AuthenticationAccess rights for users and rolesUsers with fine-grained authorization concept infono user groups or 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
HBaseMicrosoft Azure Data ExplorerTigrisVitess
DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021,  Krishna Maheshwari (sponsor) 

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase
20 October 2023, hackernoon.com

What Is HBase?
19 August 2021, IBM

HBase: The database big data left behind
6 May 2016, InfoWorld

Monitor Apache HBase on Amazon EMR using Amazon Managed Service for Prometheus and Amazon Managed ...
13 February 2023, AWS Blog

HydraBase – The evolution of HBase@Facebook
5 June 2014, Facebook Engineering

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

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

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

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

PlanetScale review: Horizontally scalable MySQL in the cloud
1 September 2021, InfoWorld

provided by Google News



Share this page

Featured Products

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

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.

Present your product here