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DBMS > Adabas vs. Google Cloud Datastore vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Vitess

System Properties Comparison Adabas vs. Google Cloud Datastore vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Vitess

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platformScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelMultivalue DBMSDocument storeRelational DBMSRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsSpatial DBMSDocument 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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.79
Rank#102  Overall
#2  Multivalue DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlcloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorervitess.io
Technical documentationcloud.google.com/­datastore/­docsdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorervitess.io/­docs
DeveloperSoftware AGGoogleHEAVY.AI, Inc.MicrosoftThe Linux Foundation, PlanetScale
Initial release19712008201620192013
Current release5.10, January 2022cloud service with continuous releases15.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAGo
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
hostedLinuxhostedDocker
Linux
macOS
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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 indexesyesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewaySQL-like query language (GQL)yesKusto Query Language (KQL), SQL subsetyes infowith proprietary extensions
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesNatural.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresin Naturalusing Google App EnginenoYes, possible languages: KQL, Python, Ryes infoproprietary syntax
TriggersnoCallbacks using the Google Apps Enginenoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaShardingSharding infoRound robinSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatorMulti-source replication using PaxosMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflownoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
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.nonoyesnoyes
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAzure Active Directory AuthenticationUsers with fine-grained authorization concept infono user groups or roles

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More resources
Adabas infodenotes "adaptable data base"Google Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerVitess
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