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DBMS > Google Cloud Bigtable vs. MonetDB vs. Splice Machine vs. Teradata Aster

System Properties Comparison Google Cloud Bigtable vs. MonetDB vs. Splice Machine vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMonetDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A relational database management system that stores data in columnsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitecloud.google.com/­bigtablewww.monetdb.orgsplicemachine.com
Technical documentationcloud.google.com/­bigtable/­docswww.monetdb.org/­Documentationsplicemachine.com/­how-it-works
DeveloperGoogleMonetDB BVSplice MachineTeradata
Initial release2015200420142005
Current releaseDec2023 (11.49), December 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoMozilla Public License 2.0Open Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava
Server operating systemshostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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.noyes infoin Aster File Store
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyes infoSQL 2003 with some extensionsyesyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes, in SQL, C, Ryes infoJavaR packages
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding via remote tablesShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesnone infoSource-replica replication available in experimental statusMulti-source replication
Source-replica replication
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integrationyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
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-standardAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableMonetDBSplice MachineTeradata Aster
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