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DBMS > BigchainDB vs. CrateDB vs. Google Cloud Datastore vs. Infobright

System Properties Comparison BigchainDB vs. CrateDB vs. Google Cloud Datastore vs. Infobright

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Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonCrateDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfobright  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsDistributed Database based on LuceneAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend
Primary database modelDocument storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document storeRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.76
Rank#216  Overall
#36  Document stores
Score0.69
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#11  Vector DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.88
Rank#198  Overall
#92  Relational DBMS
Websitewww.bigchaindb.comcratedb.comcloud.google.com/­datastoreignitetech.com/­softwarelibrary/­infobrightdb
Technical documentationbigchaindb.readthedocs.io/­en/­latestcratedb.com/­docscloud.google.com/­datastore/­docs
DeveloperCrateGoogleIgnite Technologies Inc.; formerly InfoBright Inc.
Initial release2016201320082005
Current release5.8.1, August 2024
License infoCommercial or Open SourceOpen Source infoAGPL v3Open Sourcecommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonJavaC
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedLinux
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or datenoyesyes, details hereyes
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 indexesyesyesno infoKnowledge Grid Technology used instead
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query language (GQL)yes
APIs and other access methodsCLI Client
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.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
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions (Javascript)using Google App Engineno
TriggersnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorConfigurable replication on table/partition-levelMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate 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 Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlyesrights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilities

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More resources
BigchainDBCrateDBGoogle Cloud DatastoreInfobright
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