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DBMS > Amazon Redshift vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. Neo4j vs. Quasardb

System Properties Comparison Amazon Redshift vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. Neo4j vs. Quasardb

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNeo4j  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsDistributed Event Store optimized for Internet of Things use casesFully managed big data interactive analytics platformScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsDistributed, high-performance timeseries database
Primary database modelRelational DBMSEvent Store
Time Series DBMS
Relational DBMS infocolumn orientedGraph 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
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websiteaws.amazon.com/­redshiftwww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­services/­data-explorerneo4j.comquasar.ai
Technical documentationdocs.aws.amazon.com/­redshiftwww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­en-us/­azure/­data-explorerneo4j.com/­docsdoc.quasar.ai/­master
DeveloperAmazon (based on PostgreSQL)IBMMicrosoftNeo4j, Inc.quasardb
Initial release20122017201920072009
Current release2.0cloud service with continuous releases5.20, May 20243.14.1, January 2024
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availablecommercialOpen Source infoGPL version3, commercial licenses availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageCC and C++Java, ScalaC++
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionhostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
BSD
Linux
OS X
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-free and schema-optionalschema-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-typesyesyes infointeger and binary
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.nonoyesno
Secondary indexesrestrictednoall fields are automatically indexedyes infopluggable indexing subsystem, by default Apache Luceneyes infowith tags
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardyes infothrough the embedded Spark runtimeKusto Query Language (KQL), SQL subsetnoSQL-like query language
APIs and other access methodsJDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions infoin PythonyesYes, possible languages: KQL, Python, Ryes infoUser defined Procedures and Functionsno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handlerno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceyes using Neo4j FabricSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesActive-active shard replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Causal Clustering using Raft protocol infoavailable in in Enterprise Version onlySource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnonoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes infoTransient mode
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAzure Active Directory AuthenticationUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Cryptographically strong user authentication and audit trail
More information provided by the system vendor
Amazon RedshiftIBM Db2 Event StoreMicrosoft Azure Data ExplorerNeo4jQuasardb
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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