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DBMS > Manticore Search vs. Microsoft Azure Data Explorer vs. Riak KV vs. Sadas Engine vs. VictoriaMetrics

System Properties Comparison Manticore Search vs. Microsoft Azure Data Explorer vs. Riak KV vs. Sadas Engine vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonSadas Engine  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionMulti-storage database for search, including full-text search.Fully managed big data interactive analytics platformDistributed, fault tolerant key-value storeSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelSearch engineRelational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMSTime Series DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryDocument 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
Score0.22
Rank#312  Overall
#21  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitemanticoresearch.comazure.microsoft.com/­services/­data-explorerwww.sadasengine.comvictoriametrics.com
Technical documentationmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latestwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperManticore SoftwareMicrosoftOpenSource, formerly Basho TechnologiesSADAS s.r.l.VictoriaMetrics
Initial release20172019200920062018
Current release6.0, February 2023cloud service with continuous releases3.2.0, December 20228.0v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoGPL version 2commercialOpen Source infoApache version 2, commercial enterprise editioncommercial infofree trial version availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ErlangC++Go
Server operating systemsFreeBSD
Linux
macOS
Windows
hostedLinux
OS X
AIX
Linux
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeFixed schemaFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes 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.Can index from XMLyesnonono
Secondary indexesyes infofull-text index on all search fieldsall fields are automatically indexedrestrictedyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetnoyesno
APIs and other access methodsBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
JDBC
ODBC
Proprietary protocol
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesElixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.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
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsYes, possible languages: KQL, Python, RErlangnono
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factornoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoisolated transactions for atomic changes and binary logging for safe writesnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infoThe original contents of fields are not stored in the Manticore index.yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlnoAzure Active Directory Authenticationyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standard

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More resources
Manticore SearchMicrosoft Azure Data ExplorerRiak KVSadas EngineVictoriaMetrics
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