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DBMS > Faircom DB vs. GridDB vs. Microsoft Azure Data Explorer vs. Realm vs. WakandaDB

System Properties Comparison Faircom DB vs. GridDB vs. Microsoft Azure Data Explorer vs. Realm vs. WakandaDB

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRealm  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Scalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelKey-value store
Relational DBMS
Time Series DBMSRelational DBMS infocolumn orientedDocument storeObject oriented DBMS
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
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitewww.faircom.com/­products/­faircom-dbgriddb.netazure.microsoft.com/­services/­data-explorerrealm.iowakanda.github.io
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerrealm.io/­docswakanda.github.io/­doc
DeveloperFairCom CorporationToshiba CorporationMicrosoftRealm, acquired by MongoDB in May 2019Wakanda SAS
Initial release19792013201920142012
Current releaseV12, November 20205.1, August 2022cloud service with continuous releases2.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen SourceOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++C++C++, JavaScript
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxhostedAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeschema free, schema optional, schema required, partial schema,yesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyes 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-typesyesyes
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.nonoyesnono
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetnono
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Java infowith Android only
Objective-C
React Native
Swift
JavaScript
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noYes, possible languages: KQL, Python, Rno inforuns within the applications so server-side scripts are unnecessaryyes
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingSharding infoImplicit feature of the cloud servicenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentACID at container levelnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes infoIn-Memory realmno
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users can be defined per databaseAzure Active Directory Authenticationyesyes
More information provided by the system vendor
Faircom DB infoformerly c-treeACEGridDBMicrosoft Azure Data ExplorerRealmWakandaDB
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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More resources
Faircom DB infoformerly c-treeACEGridDBMicrosoft Azure Data ExplorerRealmWakandaDB
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