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DBMS > Adabas vs. Google Cloud Bigtable vs. Graph Engine vs. HarperDB vs. Hawkular Metrics

System Properties Comparison Adabas vs. Google Cloud Bigtable vs. Graph Engine vs. HarperDB vs. Hawkular Metrics

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHarperDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelMultivalue DBMSKey-value store
Wide column store
Graph DBMS
Key-value store
Document storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.17
Rank#94  Overall
#1  Multivalue DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.55
Rank#248  Overall
#38  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlcloud.google.com/­bigtablewww.graphengine.iowww.harperdb.iowww.hawkular.org
Technical documentationcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualdocs.harperdb.io/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperSoftware AGGoogleMicrosoftHarperDBCommunity supported by Red Hat
Initial release19712015201020172014
Current release3.1, August 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMIT Licensecommercial infofree community edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CNode.jsJava
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
hosted.NETLinux
OS X
Linux
OS X
Windows
Data schemeyesschema-freeyesdynamic schemaschema-free
Typing infopredefined data types such as float or dateyesnoyesyes infoJSON 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.nonononono
Secondary indexesyesnoyesno
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewaynonoSQL-like data manipulation statementsno
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
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP REST
Supported programming languagesNaturalC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
F#
Visual Basic
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresin NaturalnoyesCustom Functions infosince release 3.1no
Triggersnonononoyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaShardinghorizontal partitioningA table resides as a whole on one (or more) nodes in a clusterSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatorInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesno
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)Access rights for users and rolesno

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More resources
Adabas infodenotes "adaptable data base"Google Cloud BigtableGraph Engine infoformer name: TrinityHarperDBHawkular Metrics
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