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DBMS > Google Cloud Bigtable vs. Snowflake vs. Splice Machine vs. Transwarp Hippo

System Properties Comparison Google Cloud Bigtable vs. Snowflake vs. Splice Machine vs. Transwarp Hippo

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonSnowflake  Xexclude from comparisonSplice Machine  Xexclude from comparisonTranswarp Hippo  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.Cloud-based data warehousing service for structured and semi-structured dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkCloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMSVector 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
Score121.33
Rank#9  Overall
#6  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.00
Rank#383  Overall
#13  Vector DBMS
Websitecloud.google.com/­bigtablewww.snowflake.comsplicemachine.comwww.transwarp.cn/­en/­subproduct/­hippo
Technical documentationcloud.google.com/­bigtable/­docsdocs.snowflake.net/­manuals/­index.htmlsplicemachine.com/­how-it-works
DeveloperGoogleSnowflake Computing Inc.Splice Machine
Initial release2015201420142023
Current release3.1, March 20211.0, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Linux
macOS
Data schemeschema-freeyes infosupport of semi-structured data formats (JSON, XML, Avro)yes
Typing infopredefined data types such as float or datenoyesyesVector, Numeric and String
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.noyesno
Secondary indexesnoyesno
SQL infoSupport of SQLnoyesyesno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
CLI Client
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Server-side scripts infoStored proceduresnouser defined functionsyes infoJavano
Triggersnono infosimilar concept for controling cloud resourcesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyesShared 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 zonesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integrationno
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDno
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.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users, groups and roles according to SQL-standardRole based access control and fine grained access rights

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More resources
Google Cloud BigtableSnowflakeSplice MachineTranswarp Hippo
DB-Engines blog posts

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Recent citations in the news

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

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27 February 2024, GeekWire

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15 December 2023, SDxCentral

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1 March 2024, Blocks & Files

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26 August 2021, The Register

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