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 > EsgynDB vs. Microsoft Azure Data Explorer vs. Newts vs. OpenTSDB

System Properties Comparison EsgynDB vs. Microsoft Azure Data Explorer vs. Newts vs. OpenTSDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNewts  Xexclude from comparisonOpenTSDB  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFully managed big data interactive analytics platformTime Series DBMS based on CassandraScalable Time Series DBMS based on HBase
Primary database modelRelational DBMSRelational DBMS infocolumn orientedTime Series DBMSTime Series 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score1.68
Rank#146  Overall
#12  Time Series DBMS
Websitewww.esgyn.cnazure.microsoft.com/­services/­data-exploreropennms.github.io/­newtsopentsdb.net
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­OpenNMS/­newts/­wikiopentsdb.net/­docs/­build/­html/­index.html
DeveloperEsgynMicrosoftOpenNMS Groupcurrently maintained by Yahoo and other contributors
Initial release2015201920142011
Current releasecloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoLGPL
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 languageC++, JavaJavaJava
Server operating systemsLinuxhostedLinux
OS X
Windows
Linux
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesnumeric data for metrics, strings for tags
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.noyesnono
Secondary indexesyesall fields are automatically indexednono
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
Java API
HTTP API
Telnet API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaErlang
Go
Java
Python
R
Ruby
Server-side scripts infoStored proceduresJava Stored ProceduresYes, possible languages: KQL, Python, Rnono
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infobased on CassandraSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on Cassandraselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency infobased on HBase
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nononono
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationnono

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
EsgynDBMicrosoft Azure Data ExplorerNewtsOpenTSDB
DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

Recent citations in the 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

Pinterest Switches from OpenTSDB to Their Own Time Series Database
16 September 2018, InfoQ.com

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

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.

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.

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

Present your product here