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DBMS > Google Cloud Bigtable vs. IBM Db2 Event Store vs. OrigoDB vs. SQL.JS vs. TerminusDB

System Properties Comparison Google Cloud Bigtable vs. IBM Db2 Event Store vs. OrigoDB vs. SQL.JS vs. TerminusDB

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonOrigoDB  Xexclude from comparisonSQL.JS  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed Event Store optimized for Internet of Things use casesA fully ACID in-memory object graph databasePort of SQLite to JavaScriptScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelKey-value store
Wide column store
Event Store
Time Series DBMS
Document store
Object oriented DBMS
Relational DBMSGraph DBMS
Secondary database modelsDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score0.63
Rank#241  Overall
#112  Relational DBMS
Score0.23
Rank#316  Overall
#27  Graph DBMS
Websitecloud.google.com/­bigtablewww.ibm.com/­products/­db2-event-storeorigodb.comsql.js.orgterminusdb.com
Technical documentationcloud.google.com/­bigtable/­docswww.ibm.com/­docs/­en/­db2-event-storeorigodb.com/­docssql.js.org/­documentation/­index.htmlterminusdb.github.io/­terminusdb/­#
DeveloperGoogleIBMRobert Friberg et alAlon Zakai infoenhancements implemented by othersDataChemist Ltd.
Initial release201520172009 infounder the name LiveDB20122018
Current release2.011.0.0, January 2023
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen SourceOpen SourceOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C#JavaScriptProlog, Rust
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionLinux
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesUser defined using .NET types and collectionsyesyes
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.nonono infocan be achieved using .NETnono
Secondary indexesnonoyes
SQL infoSupport of SQLnoyes infothrough the embedded Spark runtimenoyes infoSQL-92 is not fully supportedSQL-like query language (WOQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
.NET Client API
HTTP API
LINQ
JavaScript APIOWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.NetJavaScriptJavaScript
Python
Server-side scripts infoStored proceduresnoyesyesnoyes
Triggersnonoyes infoDomain Eventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronizednoneGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesActive-active shard replicationSource-replica replicationnoneJournaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistencynone
Foreign keys infoReferential integritynonodepending on modelyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes infoWrite ahead logno infoexcept by serializing a db to a fileyes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardRole based authorizationnoRole-based access control

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More resources
Google Cloud BigtableIBM Db2 Event StoreOrigoDBSQL.JSTerminusDB infoformer name was DataChemist
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