DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > EsgynDB vs. Greenplum vs. Microsoft Azure Data Explorer vs. PlanetScale

System Properties Comparison EsgynDB vs. Greenplum vs. Microsoft Azure Data Explorer vs. PlanetScale

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGreenplum  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPlanetScale  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAnalytic 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 platformScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedRelational DBMS
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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.49
Rank#155  Overall
#72  Relational DBMS
Websitewww.esgyn.cngreenplum.orgazure.microsoft.com/­services/­data-explorerplanetscale.com
Technical documentationdocs.greenplum.orgdocs.microsoft.com/­en-us/­azure/­data-explorerplanetscale.com/­docs
DeveloperEsgynPivotal Software Inc.MicrosoftPlanetScale
Initial release2015200520192020
Current release7.0.0, September 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaGo
Server operating systemsLinuxLinuxhostedDocker
Linux
macOS
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
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
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 4.2yes
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyesyesKusto Query Language (KQL), SQL subsetyes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
Java
Perl
Python
R
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
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 proceduresJava Stored ProceduresyesYes, possible languages: KQL, Python, Ryes infoproprietary syntax
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAzure Active Directory AuthenticationUsers 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
EsgynDBGreenplumMicrosoft Azure Data ExplorerPlanetScale
Recent citations in the news

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

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

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

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

Greenplum 6 review: Jack of all trades, master of some
7 November 2019, 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) | Azure updates
20 February 2024, Microsoft

Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates
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

PlanetScale ends free tier bid, sheds staff in profitability bid
11 March 2024, The Register

PlanetScale Ranked Number 188 Fastest-Growing Company in North America on the 2023 Deloitte Technology Fast ...
8 November 2023, businesswire.com

PlanetScale forks MySQL to add vector support
3 October 2023, TechCrunch

PlanetScale Named to Fortune 2023 Best Small Workplaces
31 August 2023, businesswire.com

How to Migrate to PlanetScale's Serverless Database
14 October 2021, The New Stack

provided by Google News



Share this page

Featured Products

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

Milvus logo

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

Present your product here