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DBMS > BigchainDB vs. BigObject vs. Brytlyt vs. Google Cloud Datastore vs. InterSystems IRIS

System Properties Comparison BigchainDB vs. BigObject vs. Brytlyt vs. Google Cloud Datastore vs. InterSystems IRIS

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonBigObject  Xexclude from comparisonBrytlyt  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInterSystems IRIS  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAnalytic DBMS for real-time computations and queriesScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability
Primary database modelDocument storeRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSDocument storeDocument store
Key-value store
Object oriented DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.82
Rank#212  Overall
#36  Document stores
Score0.13
Rank#342  Overall
#150  Relational DBMS
Score0.38
Rank#279  Overall
#126  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score4.39
Rank#81  Overall
#13  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#44  Relational DBMS
Websitewww.bigchaindb.combigobject.iobrytlyt.iocloud.google.com/­datastorewww.intersystems.com/­products/­intersystems-iris
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.bigobject.iodocs.brytlyt.iocloud.google.com/­datastore/­docsdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.cls
DeveloperBigObject, Inc.BrytlytGoogleInterSystems
Initial release20162015201620082018
Current release5.0, August 20232023.3, June 2023
License infoCommercial or Open SourceOpen Source infoAGPL v3commercial infofree community edition availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC, C++ and CUDA
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Windows
hostedAIX
Linux
macOS
Ubuntu
Windows
Data schemeschema-freeyesyesschema-freedepending on used data model
Typing infopredefined data types such as float or datenoyesyesyes, 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.nonoyes infospecific XML-type available, but no XML query functionality.noyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesSQL-like query language (GQL)yes
APIs and other access methodsCLI Client
RESTful HTTP API
fluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresLuauser defined functions infoin PL/pgSQLusing Google App Engineyes
TriggersnoyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replicationMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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.Immediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes
More information provided by the system vendor
BigchainDBBigObjectBrytlytGoogle Cloud DatastoreInterSystems IRIS
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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BigchainDBBigObjectBrytlytGoogle Cloud DatastoreInterSystems IRIS
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