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DBMS > EsgynDB vs. Hive vs. Microsoft Azure Data Explorer vs. Solr vs. TimescaleDB

System Properties Comparison EsgynDB vs. Hive vs. Microsoft Azure Data Explorer vs. Solr vs. TimescaleDB

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSolr  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache Trafodiondata warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformA widely used distributed, scalable search engine based on Apache LuceneA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedSearch engineTime 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
Spatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.esgyn.cnhive.apache.orgazure.microsoft.com/­services/­data-explorersolr.apache.orgwww.timescale.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorersolr.apache.org/­resources.htmldocs.timescale.com
DeveloperEsgynApache Software Foundation infoinitially developed by FacebookMicrosoftApache Software FoundationTimescale
Initial release20152012201920062017
Current release3.1.3, April 2022cloud service with continuous releases9.6.0, April 20242.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache Version 2Open Source infoApache 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++, JavaJavaJavaC
Server operating systemsLinuxAll OS with a Java VMhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes infoDynamic Fields enables on-the-fly addition of new fieldsyes
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 infosupports customizable data types and automatic typingnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyesyesyes
Secondary indexesyesyesall fields are automatically indexedyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSolr Parallel SQL Interfaceyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresJava Stored Proceduresyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, RJava pluginsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonooptimistic lockingACID
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.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesAzure Active Directory Authenticationyesfine grained access rights according to SQL-standard

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EsgynDBHiveMicrosoft Azure Data ExplorerSolrTimescaleDB
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