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DBMS > GridDB vs. HugeGraph vs. InfluxDB vs. Microsoft Azure Data Explorer vs. Sphinx

System Properties Comparison GridDB vs. HugeGraph vs. InfluxDB vs. Microsoft Azure Data Explorer vs. Sphinx

Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonInfluxDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA fast-speed and highly-scalable Graph DBMSDBMS for storing time series, events and metricsFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSGraph DBMSTime Series DBMSRelational DBMS infocolumn orientedSearch engine
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS infowith GEO packageDocument 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitegriddb.netgithub.com/­hugegraph
hugegraph.apache.org
www.influxdata.com/­products/­influxdb-overviewazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technical documentationdocs.griddb.nethugegraph.apache.org/­docsdocs.influxdata.com/­influxdbdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperToshiba CorporationBaiduMicrosoftSphinx Technologies Inc.
Initial release20132018201320192001
Current release5.1, August 20220.92.7.6, April 2024cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2.0Open Source infoMIT-License; commercial enterprise version availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaGoC++
Server operating systemsLinuxLinux
macOS
Unix
Linux
OS X infothrough Homebrew
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesNumeric data and Stringsyes 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.nononoyes
Secondary indexesyesyes infoalso supports composite index and range indexnoall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
HTTP API
JSON over UDP
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Groovy
Java
Python
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsnoYes, possible languages: KQL, Python, Rno
Triggersyesnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoin enterprise version onlySharding 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 infodepending on used storage backend, e.g. Cassandra and HBaseselectable replication factor infoin enterprise version onlyyes 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 jobsvia hugegraph-sparknoSpark 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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yesyesyes infoDepending on used storage engineno
User concepts infoAccess controlAccess rights for users can be defined per databaseUsers, roles and permissionssimple rights management via user accountsAzure Active Directory Authenticationno
More information provided by the system vendor
GridDBHugeGraphInfluxDBMicrosoft Azure Data ExplorerSphinx
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
InfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsGitHub trending repository
» more
Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Open source core with closed source clustering available either on-premise or on...
» more
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