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 > Amazon Redshift vs. Apache Druid vs. Apache Jena - TDB vs. Microsoft Azure Data Explorer vs. SwayDB

System Properties Comparison Amazon Redshift vs. Apache Druid vs. Apache Jena - TDB vs. Microsoft Azure Data Explorer vs. SwayDB

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonApache Druid  Xexclude from comparisonApache Jena - TDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena frameworkFully managed big data interactive analytics platformAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
RDF storeRelational DBMS infocolumn orientedKey-value store
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
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score3.62
Rank#83  Overall
#3  RDF stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websiteaws.amazon.com/­redshiftdruid.apache.orgjena.apache.org/­documentation/­tdb/­index.htmlazure.microsoft.com/­services/­data-explorerswaydb.simer.au
Technical documentationdocs.aws.amazon.com/­redshiftdruid.apache.org/­docs/­latest/­designjena.apache.org/­documentation/­tdb/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAmazon (based on PostgreSQL)Apache Software Foundation and contributorsApache Software Foundation infooriginally developed by HP LabsMicrosoftSimer Plaha
Initial release20122012200020192018
Current release29.0.1, April 20244.9.0, July 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache License, Version 2.0commercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaJavaScala
Server operating systemshostedLinux
OS X
Unix
All OS with a Java VMhosted
Data schemeyesyes infoschema-less columns are supportedyes infoRDF SchemasFixed schema with schema-less datatypes (dynamic)schema-free
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-typesno
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.nonoyesno
Secondary indexesrestrictedyesyesall fields are automatically indexedno
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL for queryingnoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
ODBC
JDBC
RESTful HTTP/JSON API
Fuseki infoREST-style SPARQL HTTP Interface
Jena RDF API
RIO infoRDF Input/Output
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Kotlin
Scala
Server-side scripts infoStored proceduresuser defined functions infoin PythonnoyesYes, possible languages: KQL, Python, Rno
Triggersnonoyes infovia event handleryes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infomanual/auto, time-basednoneSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, via HDFS, S3 or other storage enginesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoTDB TransactionsnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess control via Jena SecurityAzure Active Directory Authenticationno

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
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon RedshiftApache DruidApache Jena - TDBMicrosoft Azure Data ExplorerSwayDB
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Increased popularity for consuming DBMS services out of the cloud
2 October 2015, Paul Andlinger

show all

Recent citations in the news

Amazon Redshift Serverless is now generally available in the AWS China (Ningxia) Region
28 May 2024, AWS Blog

Build a decentralized semantic search engine on heterogeneous data stores using autonomous agents | Amazon Web ...
28 May 2024, AWS Blog

Amazon Redshift adds new AI capabilities, including Amazon Q, to boost efficiency and productivity | Amazon Web ...
29 November 2023, AWS Blog

Amazon Redshift now supports multi-data warehouse writes through data sharing (preview)
26 November 2023, AWS Blog

Amazon Redshift announces programmatic access to Advisor recommendations via API
8 February 2024, AWS Blog

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

Imply advances Apache Druid real-time analytics database
20 September 2022, TechTarget

provided by Google News

Sparql Secrets In Jena-Fuseki - DataScienceCentral.com
24 July 2022, Data Science Central

Extract and query knowledge graphs using Apache Jena (SPARQL Engine)
4 December 2019, Towards Data Science

6 Libraries in Java for Machine Learning
2 October 2023, Analytics India Magazine

A catalogue with semantic annotations makes multilabel datasets FAIR | Scientific Reports
4 May 2022, Nature.com

MarkLogic Hones Its Triple Store
18 August 2015, Datanami

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

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, Microsoft

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services
7 February 2019, 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