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DBMS > AgensGraph vs. DolphinDB vs. Microsoft Azure Data Explorer vs. Percona Server for MongoDB vs. Solr

System Properties Comparison AgensGraph vs. DolphinDB vs. Microsoft Azure Data Explorer vs. Percona Server for MongoDB vs. Solr

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonDolphinDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLDolphinDB 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.Fully managed big data interactive analytics platformA drop-in replacement for MongoDB Community Edition with enterprise-grade features.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMS
Relational DBMS
Time Series DBMSRelational DBMS infocolumn orientedDocument storeSearch 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
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.60
Rank#246  Overall
#39  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitebitnine.net/­agensgraphwww.dolphindb.comazure.microsoft.com/­services/­data-explorerwww.percona.com/­mongodb/­software/­percona-server-for-mongodbsolr.apache.org
Technical documentationbitnine.net/­documentationdocs.dolphindb.cn/­en/­help200/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.percona.com/­percona-distribution-for-mongodbsolr.apache.org/­resources.html
DeveloperBitnine Global Inc.DolphinDB, IncMicrosoftPerconaApache Software Foundation
Initial release20162018201920152006
Current release2.1, December 2018v2.00.4, January 2022cloud service with continuous releases3.4.10-2.10, November 20179.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercial infofree community version availablecommercialOpen Source infoGPL Version 2Open Source infoApache Version 2
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 languageCC++C++Java
Server operating systemsLinux
OS X
Windows
Linux
Windows
hostedLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemedepending on used data modelyesFixed schema with schema-less datatypes (dynamic)schema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
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 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.nonoyesnoyes
Secondary indexesyesyesall fields are automatically indexedyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesSQL-like query languageKusto Query Language (KQL), SQL subsetnoSolr Parallel SQL Interface
APIs and other access methodsCypher Query Language
JDBC
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
proprietary protocol using JSONJava API
RESTful HTTP/JSON API
Supported programming languagesC
Java
JavaScript
Python
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesyesYes, possible languages: KQL, Python, RJavaScriptJava plugins
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancehorizontal partitioningSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnonooptimistic 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.noyesnoyes infovia In-Memory Engineyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAdministrators, Users, GroupsAzure Active Directory AuthenticationAccess rights for users and rolesyes

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More resources
AgensGraphDolphinDBMicrosoft Azure Data ExplorerPercona Server for MongoDBSolr
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