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DBMS > Google Cloud Bigtable vs. IBM Db2 Event Store vs. RDFox vs. Splice Machine

System Properties Comparison Google Cloud Bigtable vs. IBM Db2 Event Store vs. RDFox vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRDFox  Xexclude from comparisonSplice Machine  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 casesHigh performance knowledge graph and semantic reasoning engineOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Wide column store
Event Store
Time Series DBMS
Graph DBMS
RDF store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitecloud.google.com/­bigtablewww.ibm.com/­products/­db2-event-storewww.oxfordsemantic.techsplicemachine.com
Technical documentationcloud.google.com/­bigtable/­docswww.ibm.com/­docs/­en/­db2-event-storedocs.oxfordsemantic.techsplicemachine.com/­how-it-works
DeveloperGoogleIBMOxford Semantic TechnologiesSplice Machine
Initial release2015201720172014
Current release2.06.0, Septermber 20223.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++Java
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionLinux
macOS
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyes infoRDF schemasyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nono
Secondary indexesnonoyes
SQL infoSupport of SQLnoyes infothrough the embedded Spark runtimenoyes
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
RESTful HTTP API
SPARQL 1.1
JDBC
Native Spark Datasource
ODBC
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
C
Java
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyes infoJava
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar 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 replicationreplication via a shared file systemMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
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-standardRoles, resources, and access typesAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud BigtableIBM Db2 Event StoreRDFoxSplice Machine
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