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DBMS > Google Cloud Bigtable vs. gStore vs. Splice Machine vs. Sqrrl

System Properties Comparison Google Cloud Bigtable vs. gStore vs. Splice Machine vs. Sqrrl

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisongStore  Xexclude from comparisonSplice Machine  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been 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 native Graph DBMS to store and maintain very large RDF datasets.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value store
Wide column store
Graph DBMS
RDF store
Relational DBMSDocument store
Graph DBMS
Key-value store
Wide column 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
Score0.14
Rank#342  Overall
#34  Graph DBMS
#16  RDF stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitecloud.google.com/­bigtableen.gstore.cnsplicemachine.comsqrrl.com
Technical documentationcloud.google.com/­bigtable/­docsen.gstore.cn/­#/­enDocssplicemachine.com/­how-it-works
DeveloperGoogleSplice MachineAmazon infooriginally Sqrrl Data, Inc.
Initial release2015201620142012
Current release1.2, November 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemshostedLinuxLinux
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-free and OWL/RDFS-schema supportyesschema-free
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 indexesnoyesyes
SQL infoSupport of SQLnonoyesno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
SPARQL 1.1
JDBC
Native Spark Datasource
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyesyes infoJavano
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar PartitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integrationyes
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 infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsyesACIDAtomic updates per row, document, or graph entity
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissions, Role-Based Access Control (RBAC) supportedAccess rights for users, groups and roles according to SQL-standardCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Google Cloud BigtablegStoreSplice MachineSqrrl
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