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

DBMS > Apache Druid vs. Greenplum vs. Microsoft Azure Data Explorer vs. Sequoiadb vs. STSdb

System Properties Comparison Apache Druid vs. Greenplum vs. Microsoft Azure Data Explorer vs. Sequoiadb vs. STSdb

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGreenplum  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSequoiadb  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Fully managed big data interactive analytics platformNewSQL database with distributed OLTP and SQLKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn orientedDocument store
Relational DBMS
Key-value store
Secondary database modelsDocument store
Spatial DBMS
Document 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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitedruid.apache.orggreenplum.orgazure.microsoft.com/­services/­data-explorerwww.sequoiadb.comgithub.com/­STSSoft/­STSdb4
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.greenplum.orgdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software Foundation and contributorsPivotal Software Inc.MicrosoftSequoiadb Ltd.STS Soft SC
Initial release20122005201920132011
Current release29.0.1, April 20247.0.0, September 2023cloud service with continuous releases4.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0commercialOpen Source infoServer: AGPL; Client: Apache V2Open Source infoGPLv2, commercial license available
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 languageJavaC++C#
Server operating systemsLinux
OS X
Unix
LinuxhostedLinuxWindows
Data schemeyes infoschema-less columns are supportedyesFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infooid, date, timestamp, binary, regexyes infoprimitive types and user defined types (classes)
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.noyes infosince Version 4.2yesno
Secondary indexesyesyesall fields are automatically indexedyesno
SQL infoSupport of SQLSQL for queryingyesKusto Query Language (KQL), SQL subsetSQL-like query languageno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
proprietary protocol using JSON.NET Client API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
Java
Perl
Python
R
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Java
PHP
Python
C#
Java
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, RJavaScriptno
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoDocument is locked during a transactionno
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.nononono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAzure Active Directory Authenticationsimple password-based access controlno

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
Apache DruidGreenplumMicrosoft Azure Data ExplorerSequoiadbSTSdb
Recent citations in the 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

Imply Announces Automatic Schema Discovery for Apache Druid, Reinforcing Druid's Leadership for Real-Time ...
6 June 2023, Business Wire

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

provided by Google News

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services
9 September 2019, AWS Blog

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
6 December 2018, oreilly.com

RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

Greenplum 6 ventures outside the analytic box
19 March 2019, ZDNet

Greenplum 6 review: Jack of all trades, master of some
7 November 2019, InfoWorld

provided by Google News

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

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

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

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

Log and Telemetry Analytics Performance Benchmark
16 August 2022, Gigaom

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

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

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

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here