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DBMS > Adabas vs. Badger vs. CrateDB vs. Lovefield

System Properties Comparison Adabas vs. Badger vs. CrateDB vs. Lovefield

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Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonBadger  Xexclude from comparisonCrateDB  Xexclude from comparisonLovefield  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Distributed Database based on LuceneEmbeddable relational database for web apps written in pure JavaScript
Primary database modelMultivalue DBMSKey-value storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#87  Overall
#1  Multivalue DBMS
Score0.25
Rank#315  Overall
#46  Key-value stores
Score0.76
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#18  Time Series DBMS
#8  Vector DBMS
Score0.35
Rank#286  Overall
#131  Relational DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlgithub.com/­dgraph-io/­badgercratedb.comgoogle.github.io/­lovefield
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercratedb.com/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperSoftware AGDGraph LabsCrateGoogle
Initial release1971201720132014
Current release2.1.12, February 2017
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageGoJavaJavaScript
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
BSD
Linux
OS X
Solaris
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safari
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL Gatewaynoyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query language infovia JavaScript builder pattern
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
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Supported programming languagesNaturalGo.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
JavaScript
Server-side scripts infoStored proceduresin Naturalnouser defined functions (Javascript)no
TriggersnononoUsing read-only observers
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistanoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatornoneConfigurable replication on table/partition-levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Database
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes infousing MemoryDB
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)norights management via user accountsno
More information provided by the system vendor
Adabas infodenotes "adaptable data base"BadgerCrateDBLovefield
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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Adabas infodenotes "adaptable data base"BadgerCrateDBLovefield
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