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DBMS > BigchainDB vs. Google Cloud Datastore vs. IBM Db2 Event Store vs. Kinetica

System Properties Comparison BigchainDB vs. Google Cloud Datastore vs. IBM Db2 Event Store vs. Kinetica

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Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed Event Store optimized for Internet of Things use casesFully vectorized database across both GPUs and CPUs
Primary database modelDocument storeDocument storeEvent Store
Time Series DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
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
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitewww.bigchaindb.comcloud.google.com/­datastorewww.ibm.com/­products/­db2-event-storewww.kinetica.com
Technical documentationbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2-event-storedocs.kinetica.com
DeveloperGoogleIBMKinetica
Initial release2016200820172012
Current release2.07.1, August 2021
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialcommercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC and C++C, C++
Server operating systemsLinuxhostedLinux infoLinux, macOS, Windows for the developer additionLinux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes, details hereyesyes
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 indexesyesnoyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yes infothrough the embedded Spark runtimeSQL-like DML and DDL statements
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresusing Google App Engineyesuser defined functions
TriggersCallbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using PaxosActive-active shard replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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.Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
BigchainDBGoogle Cloud DatastoreIBM Db2 Event StoreKinetica
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