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

DBMS > DolphinDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Netezza vs. Warp 10

System Properties Comparison DolphinDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Netezza vs. Warp 10

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platformData warehouse and analytics appliance part of IBM PureSystemsTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Relational DBMS infocolumn orientedRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMSDocument 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
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.dolphindb.comwww.graphengine.ioazure.microsoft.com/­services/­data-explorerwww.ibm.com/­products/­netezzawww.warp10.io
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerwww.warp10.io/­content/­02_Getting_started
DeveloperDolphinDB, IncMicrosoftMicrosoftIBMSenX
Initial release20182010201920002015
Current releasev2.00.4, January 2022cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoMIT LicensecommercialcommercialOpen Source infoApache License 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 languageC++.NET and CJava
Server operating systemsLinux
Windows
.NEThostedLinux infoincluded in applianceLinux
OS X
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesschema-free
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-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.nonoyesno
Secondary indexesyesall fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like query languagenoKusto Query Language (KQL), SQL subsetyesno
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
OLE DB
HTTP API
Jupyter
WebSocket
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyesyesYes, possible languages: KQL, Python, Ryesyes infoWarpScript
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioningSharding infoImplicit feature of the cloud serviceShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlAdministrators, Users, GroupsAzure Active Directory AuthenticationUsers with fine-grained authorization conceptMandatory use of cryptographic tokens, containing fine-grained authorizations

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
DolphinDBGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerNetezza infoAlso called PureData System for Analytics by IBMWarp 10
Recent citations in the news

Trinity
2 June 2023, microsoft.com

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

How Google and Microsoft taught search to "understand" the Web
6 June 2012, Ars Technica

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

provided by Google News

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, azure.microsoft.com

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

General availability: New KQL function to enrich your data analysis with geographic context | Azure updates
6 June 2023, azure.microsoft.com

Azure Data Explorer and Stream Analytics for anomaly detection
16 January 2020, azure.microsoft.com

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, azure.microsoft.com

provided by Google News

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

provided by Google News

Time Series Databases Software Market - A comprehensive study by Key Players | Warp 10, Amazon Timestream ...
6 February 2020, openPR

Launched Just A Year Ago, Open-Source Scality S3 Server Gains Extraordinary Momentum As It Simplifies The Life Of ...
28 June 2017, PR Newswire UK

Time Series Databases Software market latest trends, CAGR, and forecast till 2026 | eSherpa Market Reports
13 April 2020, openPR

Time Series Intelligence Software Market Business Insights, Key Trend Analysis | Google, SAP, Azure Time Series ...
24 April 2024, Amoré

provided by Google News



Share this page

Featured Products

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

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