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DBMS > Adabas vs. FoundationDB vs. GridGain vs. Hive vs. Microsoft Azure Data Explorer

System Properties Comparison Adabas vs. FoundationDB vs. GridGain vs. Hive vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonFoundationDB  Xexclude from comparisonGridGain  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformOrdered key-value store. Core features are complimented by layers.GridGain is an in-memory computing platform, built on Apache Ignitedata warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platform
Primary database modelMultivalue DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn oriented
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.79
Rank#102  Overall
#2  Multivalue DBMS
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlgithub.com/­apple/­foundationdbwww.gridgain.comhive.apache.orgazure.microsoft.com/­services/­data-explorer
Technical documentationapple.github.io/­foundationdbwww.gridgain.com/­docs/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperSoftware AGFoundationDBGridGain Systems, Inc.Apache Software Foundation infoinitially developed by FacebookMicrosoft
Initial release19712013200720122019
Current release6.2.28, November 2020GridGain 8.5.13.1.3, April 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, C++, .NetJava
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
All OS with a Java VMhosted
Data schemeyesschema-free infosome layers support schemasyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesno infosome layers support typingyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.noyesyes
Secondary indexesyesnoyesyesall fields are automatically indexed
SQL infoSupport of SQLyes infowith add-on product Adabas SQL Gatewaysupported in specific SQL layer onlyANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subset
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesNatural.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresin Naturalin SQL-layer onlyyes (compute grid and cache interceptors can be used instead)yes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, R
Triggersnonoyes (cache interceptors and events)noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event Replicatoryesyes (replicated cache)selectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)yes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoin SQL-layer onlynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)noSecurity Hooks for custom implementationsAccess rights for users, groups and rolesAzure Active Directory Authentication

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More resources
Adabas infodenotes "adaptable data base"FoundationDBGridGainHiveMicrosoft Azure Data Explorer
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