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DBMS > Amazon Redshift vs. Ignite vs. Microsoft Azure Data Explorer vs. Riak KV vs. Titan

System Properties Comparison Amazon Redshift vs. Ignite vs. Microsoft Azure Data Explorer vs. Riak KV vs. Titan

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionLarge scale data warehouse service for use with business intelligence toolsApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformDistributed, fault tolerant key-value storeTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesGraph 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
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websiteaws.amazon.com/­redshiftignite.apache.orgazure.microsoft.com/­services/­data-explorergithub.com/­thinkaurelius/­titan
Technical documentationdocs.aws.amazon.com/­redshiftapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latestgithub.com/­thinkaurelius/­titan/­wiki
DeveloperAmazon (based on PostgreSQL)Apache Software FoundationMicrosoftOpenSource, formerly Basho TechnologiesAurelius, owned by DataStax
Initial release20122015201920092012
Current releaseApache Ignite 2.6cloud service with continuous releases3.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache license, version 2.0
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.
Implementation languageCC++, Java, .NetErlangJava
Server operating systemshostedLinux
OS X
Solaris
Windows
hostedLinux
OS X
Linux
OS X
Unix
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-freeyes
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-typesnoyes
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.noyesyesno
Secondary indexesrestrictedyesall fields are automatically indexedrestrictedyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Clojure
Java
Python
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, RErlangyes
Triggersnoyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"yes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparkyesyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnonono infolinks between data sets can be storedyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsAzure Active Directory Authenticationyes, using Riak SecurityUser authentification and security via Rexster Graph Server

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Amazon RedshiftIgniteMicrosoft Azure Data ExplorerRiak KVTitan
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