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DBMS > Google Cloud Bigtable vs. H2GIS vs. Oracle Coherence vs. Vitess

System Properties Comparison Google Cloud Bigtable vs. H2GIS vs. Oracle Coherence vs. Vitess

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonH2GIS  Xexclude from comparisonOracle Coherence  Xexclude from comparisonVitess  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.Spatial extension of H2Oracles in-memory data grid solutionScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelKey-value store
Wide column store
Spatial DBMSKey-value storeRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
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
Score0.08
Rank#368  Overall
#7  Spatial DBMS
Score1.97
Rank#129  Overall
#22  Key-value stores
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitecloud.google.com/­bigtablewww.h2gis.orgwww.oracle.com/­java/­coherencevitess.io
Technical documentationcloud.google.com/­bigtable/­docswww.h2gis.org/­docs/­homedocs.oracle.com/­en/­middleware/­standalone/­coherencevitess.io/­docs
DeveloperGoogleCNRSOracleThe Linux Foundation, PlanetScale
Initial release2015201320072013
Current release14.1, August 202315.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoLGPL 3.0commercialOpen Source infoApache Version 2.0, commercial licenses available
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 languageJavaJavaGo
Server operating systemshostedAll OS with a Java VMDocker
Linux
macOS
Data schemeschema-freeyesschema-freeyes
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.nonono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyesnoyes infowith proprietary extensions
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Java.Net
C++
Java
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infobased on H2noyes infoproprietary syntax
Triggersnoyesyes infoLive Eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infobased on H2yes, with selectable consistency levelMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDconfigurableACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes infooptionallyyes
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)yes infobased on H2authentification to access the cache via certificates or http basic authenticationUsers with fine-grained authorization concept infono user groups or roles

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More resources
Google Cloud BigtableH2GISOracle CoherenceVitess
Recent citations in the news

Google says it'll stop charging fees to transfer data out of Google Cloud
11 January 2024, TechCrunch

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

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20 December 2012, Oracle

Oracle releases free open source Oracle Coherence community edition
28 June 2020, iTWire

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15 October 2020, Oracle

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PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News



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