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DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. DolphinDB vs. HBase vs. Microsoft Azure Data Explorer vs. Solr

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. DolphinDB vs. HBase vs. Microsoft Azure Data Explorer vs. Solr

Editorial information provided by DB-Engines
NameAlibaba Cloud AnalyticDB for PostgreSQL infoformer name was HybridDB  Xexclude from comparisonDolphinDB  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAn online MPP (Massively Parallel Processing) data warehousing service based on GreenplumDolphinDB 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.Wide-column store based on Apache Hadoop and on concepts of BigTableFully managed big data interactive analytics platformA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSTime Series DBMSWide column storeRelational DBMS infocolumn orientedSearch engine
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.68
Rank#231  Overall
#105  Relational DBMS
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.alibabacloud.com/­product/­hybriddb-postgresqlwww.dolphindb.comhbase.apache.orgazure.microsoft.com/­services/­data-explorersolr.apache.org
Technical documentationwww.alibabacloud.com/­help/­en/­analyticdb-for-postgresql/­latest/­product-introduction-overviewdocs.dolphindb.cn/­en/­help200/­index.htmlhbase.apache.org/­book.htmldocs.microsoft.com/­en-us/­azure/­data-explorersolr.apache.org/­resources.html
DeveloperAlibaba / Pivotal Software Inc. / PostgreSQL Global Development GroupDolphinDB, IncApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftApache Software Foundation
Initial release20162018200820192006
Current releasev2.00.4, January 20222.3.4, January 2021cloud service with continuous releases9.6.0, April 2024
License infoCommercial or Open Sourcecommercialcommercial infofree community version availableOpen Source infoApache version 2commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJava
Server operating systemshostedLinux
Windows
Linux
Unix
Windows infousing Cygwin
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesschema-free, schema definition possibleFixed schema with schema-less datatypes (dynamic)yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes 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 typing
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.yesnonoyesyes
Secondary indexesyesyesnoall fields are automatically indexedyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesSQL-like query languagenoKusto Query Language (KQL), SQL subsetSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Java API
RESTful HTTP API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesC
Java
Perl
Python
R
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C
C#
C++
Groovy
Java
PHP
Python
Scala
.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
Server-side scripts infoStored proceduresyesyesyes infoCoprocessors in JavaYes, possible languages: KQL, Python, RJava plugins
Triggersyesnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioningShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyesMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesSingle row ACID (across millions of columns)nooptimistic locking
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.noyesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAdministrators, Users, GroupsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAzure Active Directory Authenticationyes

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More resources
Alibaba Cloud AnalyticDB for PostgreSQL infoformer name was HybridDBDolphinDBHBaseMicrosoft Azure Data ExplorerSolr
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