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DBMS > BigchainDB vs. Google Cloud Datastore vs. Hazelcast vs. Lovefield vs. Trafodion

System Properties Comparison BigchainDB vs. Google Cloud Datastore vs. Hazelcast vs. Lovefield vs. Trafodion

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonLovefield  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridEmbeddable relational database for web apps written in pure JavaScriptTransactional SQL-on-Hadoop DBMS
Primary database modelDocument storeDocument storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.33
Rank#286  Overall
#131  Relational DBMS
Websitewww.bigchaindb.comcloud.google.com/­datastorehazelcast.comgoogle.github.io/­lovefieldtrafodion.apache.org
Technical documentationbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­datastore/­docshazelcast.org/­imdg/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdtrafodion.apache.org/­documentation.html
DeveloperGoogleHazelcastGoogleApache Software Foundation, originally developed by HP
Initial release20162008200820142014
Current release5.3.6, November 20232.1.12, February 20172.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonJavaJavaScriptC++, Java
Server operating systemsLinuxhostedAll OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes, details hereyesyesyes
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 infothe object must implement a serialization strategynono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languageSQL-like query language infovia JavaScript builder patternyes
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
JavaScriptAll languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresusing Google App Engineyes infoEvent Listeners, Executor ServicesnoJava Stored Procedures
TriggersCallbacks using the Google Apps Engineyes infoEventsUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosyes infoReplicated Mapnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDBno
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlnofine grained access rights according to SQL-standard

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More resources
BigchainDBGoogle Cloud DatastoreHazelcastLovefieldTrafodion
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