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DBMS > AgensGraph vs. EDB Postgres vs. Microsoft Azure Data Explorer vs. Solr vs. Sqrrl

System Properties Comparison AgensGraph vs. EDB Postgres vs. Microsoft Azure Data Explorer vs. Solr vs. Sqrrl

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonEDB Postgres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Fully managed big data interactive analytics platformA widely used distributed, scalable search engine based on Apache LuceneAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store
Spatial DBMS
Document 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
Score0.16
Rank#333  Overall
#30  Graph DBMS
#146  Relational DBMS
Score2.18
Rank#122  Overall
#59  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Websitebitnine.net/­agensgraphwww.enterprisedb.comazure.microsoft.com/­services/­data-explorersolr.apache.orgsqrrl.com
Technical documentationbitnine.net/­documentationwww.enterprisedb.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorersolr.apache.org/­resources.html
DeveloperBitnine Global Inc.EnterpriseDBMicrosoftApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release20162005201920062012
Current release2.1, December 201814, December 2021cloud service with continuous releases9.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercial infoBSD for PostgreSQL-componentscommercialOpen Source infoApache Version 2commercial
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 languageCCJavaJava
Server operating systemsLinux
OS X
Windows
Linux
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemedepending on used data modelyesFixed schema with schema-less datatypes (dynamic)yes infoDynamic Fields enables on-the-fly addition of new fieldsschema-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-typesyes infosupports customizable data types and automatic typingyes
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.noyes infospecific XML-type available, but no XML query functionality.yesyes
Secondary indexesyesyesall fields are automatically indexedyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesyes infostandard with numerous extensionsKusto Query Language (KQL), SQL subsetSolr Parallel SQL Interfaceno
APIs and other access methodsCypher Query Language
JDBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
Java
JavaScript
Python
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.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
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Yes, possible languages: KQL, Python, RJava pluginsno
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancehorizontal partitioning infoby hash, list or rangeSharding infoImplicit feature of the cloud serviceShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic lockingAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAzure Active Directory AuthenticationyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
AgensGraphEDB PostgresMicrosoft Azure Data ExplorerSolrSqrrl
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