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DBMS > Microsoft Azure Data Explorer vs. Oracle vs. Redis vs. Sphinx vs. Trino

System Properties Comparison Microsoft Azure Data Explorer vs. Oracle vs. Redis vs. Sphinx vs. Trino

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonOracle  Xexclude from comparisonRedis  Xexclude from comparisonSphinx  Xexclude from comparisonTrino  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformWidely used RDBMSPopular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments infoRedis focuses on performance so most of its design decisions prioritize high performance and very low latencies.Open source search engine for searching in data from different sources, e.g. relational databasesFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelRelational DBMS infocolumn orientedRelational DBMSKey-value store infoMultiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistenceSearch engineRelational 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
Document store
Graph DBMS infowith Oracle Spatial and Graph
RDF store infowith Oracle Spatial and Graph
Spatial DBMS infowith Oracle Spatial and Graph
Vector DBMS infosince Oracle 23
Document store infowith RedisJSON
Graph DBMS infowith RedisGraph
Spatial DBMS
Search engine infowith RediSearch
Time Series DBMS infowith RedisTimeSeries
Vector DBMS
Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1244.08
Rank#1  Overall
#1  Relational DBMS
Score155.94
Rank#6  Overall
#1  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Score4.99
Rank#65  Overall
#36  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerwww.oracle.com/­databaseredis.com
redis.io
sphinxsearch.comtrino.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­databasedocs.redis.com/­latest/­index.html
redis.io/­docs
sphinxsearch.com/­docstrino.io/­broadcast
trino.io/­docs/­current
Social network pagesLinkedInTwitterYouTubeGitHub
DeveloperMicrosoftOracleRedis project core team, inspired by Salvatore Sanfilippo infoDevelopment sponsored by Redis Inc.Sphinx Technologies Inc.Trino Software Foundation
Initial release20191980200920012012 info2020 rebranded from PrestoSQL
Current releasecloud service with continuous releases23c, September 20237.2.5, May 20243.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infosource-available extensions (modules), commercial licenses for Redis EnterpriseOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.
Implementation languageC and C++CC++Java
Server operating systemshostedAIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS
BSD
Linux
OS X
Windows infoported and maintained by Microsoft Open Technologies, Inc.
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS infofor devlopment
Data schemeFixed schema with schema-less datatypes (dynamic)yes infoSchemaless in JSON and XML columnsschema-freeyesyes
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesnoyes
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.yesyesnono
Secondary indexesall fields are automatically indexedyesyes infowith RediSearch moduleyes infofull-text index on all search fieldsdepending on connected data-source
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyes infowith proprietary extensionswith RediSQL moduleSQL-like query language (SphinxQL)yes
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
proprietary protocol infoRESP - REdis Serialization ProtocolProprietary protocolJDBC
RESTful HTTP API
Trino CLI
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RPL/SQL infoalso stored procedures in Java possibleLua; Redis Functions coming in Redis 7 (slides and Github)noyes, depending on connected data-source
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyespublish/subscribe channels provide some trigger functionality; RedisGearsnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningSharding infoAutomatic hash-based sharding with support for hash-tags for manual shardingSharding infoPartitioning is done manually, search queries against distributed index is supporteddepending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
Multi-source replication infowith Redis Enterprise Pack
Source-replica replication infoChained replication is supported
nonedepending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan be realized in PL/SQLthrough RedisGearsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active
depending on connected data-source
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoisolation level can be parameterizedAtomic execution of command blocks and scripts and optimistic lockingnodepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoData access is serialized by the serveryesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes infoThe original contents of fields are not stored in the Sphinx index.depending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoVersion 12c introduced the new option 'Oracle Database In-Memory'yes
User concepts infoAccess controlAzure Active Directory Authenticationfine grained access rights according to SQL-standardAccess Control Lists (ACLs): redis.io/­docs/­management/­security/­acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/­docs/­management/­security/­encryption
Password-based authentication
noSQL standard access control
More information provided by the system vendor
Microsoft Azure Data ExplorerOracleRedisSphinxTrino
Specific characteristicsTrino is the fastest open source, massively parallel processing SQL query engine...
» more
Competitive advantagesHigh performance analtyics and data processing of very large data sets Powerful ANSI...
» more
Typical application scenariosPerformant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more
Key customersTrino is widely adopted across the globe as freely-available open source software....
» more
Market metrics33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more
Licensing and pricing modelsTrino is an open source project and usage is therefore free. Commercial offerings...
» more
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More resources
Microsoft Azure Data ExplorerOracleRedisSphinxTrino
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