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DBMS > Adabas vs. Databricks vs. Google Cloud Bigtable vs. Riak TS vs. Tkrzw

System Properties Comparison Adabas vs. Databricks vs. Google Cloud Bigtable vs. Riak TS vs. Tkrzw

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRiak TS  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KVA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelMultivalue DBMSDocument store
Relational DBMS
Key-value store
Wide column store
Time Series DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.79
Rank#102  Overall
#2  Multivalue DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.28
Rank#307  Overall
#27  Time Series DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlwww.databricks.comcloud.google.com/­bigtabledbmx.net/­tkrzw
Technical documentationdocs.databricks.comcloud.google.com/­bigtable/­docswww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperSoftware AGDatabricksGoogleOpen Source, formerly Basho TechnologiesMikio Hirabayashi
Initial release19712013201520152020
Current release3.0.0, September 20220.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen SourceOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
hostedhostedLinux
OS X
Linux
macOS
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnonono
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.noyesnonono
Secondary indexesyesyesnorestricted
SQL infoSupport of SQLyes infowith add-on product Adabas SQL Gatewaywith Databricks SQLnoyes, limitedno
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
JDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Native Erlang Interface
Supported programming languagesNaturalPython
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresin Naturaluser defined functions and aggregatesnoErlangno
Triggersnonoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatoryesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsno
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.nononoyes infousing specific database classes
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)nono
More information provided by the system vendor
Adabas infodenotes "adaptable data base"DatabricksGoogle Cloud BigtableRiak TSTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Adabas infodenotes "adaptable data base"DatabricksGoogle Cloud BigtableRiak TSTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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