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DBMS > GridDB vs. Microsoft Azure Data Explorer vs. ReductStore vs. Sphinx

System Properties Comparison GridDB vs. Microsoft Azure Data Explorer vs. ReductStore vs. Sphinx

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonReductStore  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedTime Series DBMSSearch engine
Secondary database modelsKey-value store
Relational 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitegriddb.netazure.microsoft.com/­services/­data-explorergithub.com/­reductstore
www.reduct.store
sphinxsearch.com
Technical documentationdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerwww.reduct.store/­docssphinxsearch.com/­docs
DeveloperToshiba CorporationMicrosoftReductStore LLCSphinx Technologies Inc.
Initial release2013201920232001
Current release5.1, August 2022cloud service with continuous releases1.9, March 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoBusiness Source License 1.1Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, RustC++
Server operating systemsLinuxhostedDocker
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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
Secondary indexesyesall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP APIProprietary protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
JavaScript (Node.js)
Python
Rust
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rno
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users can be defined per databaseAzure Active Directory Authenticationno
More information provided by the system vendor
GridDBMicrosoft Azure Data ExplorerReductStoreSphinx
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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GridDBMicrosoft Azure Data ExplorerReductStoreSphinx
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