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DBMS > Adabas vs. IBM Db2 Event Store vs. Lovefield vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB

System Properties Comparison Adabas vs. IBM Db2 Event Store vs. Lovefield vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformDistributed Event Store optimized for Internet of Things use casesEmbeddable relational database for web apps written in pure JavaScriptFully managed big data interactive analytics platformWidely used in-process key-value store
Primary database modelMultivalue DBMSEvent Store
Time Series DBMS
Relational DBMSRelational DBMS infocolumn orientedKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
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
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlwww.ibm.com/­products/­db2-event-storegoogle.github.io/­lovefieldazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storegithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperSoftware AGIBMGoogleMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release19712017201420191994
Current release2.02.1.12, February 2017cloud service with continuous releases18.1.40, May 2020
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen Source infoApache 2.0commercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++JavaScriptC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
Linux infoLinux, macOS, Windows for the developer additionserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes 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.nononoyesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL Gatewayyes infothrough the embedded Spark runtimeSQL-like query language infovia JavaScript builder patternKusto Query Language (KQL), SQL subsetyes infoSQL interfaced based on SQLite is available
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesNaturalC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresin NaturalyesnoYes, possible languages: KQL, Python, Rno
TriggersnonoUsing read-only observersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaShardingnoneSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatorActive-active shard replicationnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDBnoyes
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)fine grained access rights according to SQL-standardnoAzure Active Directory Authenticationno

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More resources
Adabas infodenotes "adaptable data base"IBM Db2 Event StoreLovefieldMicrosoft Azure Data ExplorerOracle Berkeley DB
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