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DBMS > Adabas vs. Bangdb vs. CrateDB vs. Fauna vs. Google Cloud Datastore

System Properties Comparison Adabas vs. Bangdb vs. CrateDB vs. Fauna vs. Google Cloud Datastore

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonBangdb  Xexclude from comparisonCrateDB  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformConverged and high performance database for device data, events, time series, document and graphDistributed Database based on LuceneFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelMultivalue DBMSDocument store
Graph DBMS
Time Series DBMS
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Document store
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.79
Rank#102  Overall
#2  Multivalue DBMS
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlbangdb.comcratedb.comfauna.comcloud.google.com/­datastore
Technical documentationdocs.bangdb.comcratedb.com/­docsdocs.fauna.comcloud.google.com/­datastore/­docs
DeveloperSoftware AGSachin Sinha, BangDBCrateFauna, Inc.Google
Initial release19712012201320142008
Current releaseBangDB 2.0, October 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSD 3Open Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
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 languageC, C++JavaScala
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
LinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedhosted
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesnoyes, details here
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 indexesyesyes infosecondary, composite, nested, reverse, geospatialyesyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewaySQL like support with command line toolyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL-like query language (GQL)
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
Proprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesNaturalC
C#
C++
Java
Python
.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
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresin Naturalnouser defined functions (Javascript)user defined functionsusing Google App Engine
Triggersnoyes, Notifications (with Streaming only)nonoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardinghorizontal partitioning infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event Replicatorselectable replication factor, Knob for CAP (enterprise version only)Configurable replication on table/partition-levelMulti-source replicationMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable consistency, set CAP knob accordinglyEventual Consistency
Read-after-write consistency on record level
Immediate 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.
Foreign keys infoReferential integritynononoyesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, run db with in-memory only modenonono
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)yes (enterprise version only)rights management via user accountsIdentity management, authentication, and access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
Adabas infodenotes "adaptable data base"BangdbCrateDBFauna infopreviously named FaunaDBGoogle Cloud Datastore
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"BangdbCrateDBFauna infopreviously named FaunaDBGoogle Cloud Datastore
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