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DBMS > Google Cloud Spanner vs. Graphite vs. Heroic vs. Vitess

System Properties Comparison Google Cloud Spanner vs. Graphite vs. Heroic vs. Vitess

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonGraphite  Xexclude from comparisonHeroic  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitecloud.google.com/­spannergithub.com/­graphite-project/­graphite-webgithub.com/­spotify/­heroicvitess.io
Technical documentationcloud.google.com/­spanner/­docsgraphite.readthedocs.iospotify.github.io/­heroicvitess.io/­docs
DeveloperGoogleChris DavisSpotifyThe Linux Foundation, PlanetScale
Initial release2017200620142013
Current release15.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open 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

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Implementation languagePythonJavaGo
Server operating systemshostedLinux
Unix
Docker
Linux
macOS
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes
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 indexesyesnoyes infovia Elasticsearchyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011nonoyes infowith proprietary extensions
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP API
Sockets
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
JavaScript (Node.js)
Python
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 proceduresnononoyes infoproprietary syntax
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.noneyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationnonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes infolockingyesyes infotable locks or row locks depending on storage engine
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)noUsers with fine-grained authorization concept infono user groups or roles

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More resources
Google Cloud SpannerGraphiteHeroicVitess
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Recent citations in the news

Google Improves Cloud Spanner: More Compute and Storage without Price Increase
14 October 2023, InfoQ.com

Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB
11 October 2023, TechCrunch

Google makes its Cloud Spanner database service faster and more cost-efficient
11 October 2023, SiliconANGLE News

Google Spanner: When Do You Need to Move to It?
11 September 2023, hackernoon.com

Google Cloud Spanner competes directly with Amazon DynamoDB
12 October 2023, Techzine Europe

provided by Google News

Grafana Labs Announces Mimir Time Series Database
1 April 2022, Datanami

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

The value of time series data and TSDBs
10 June 2021, InfoWorld

Getting Started with Infrastructure Monitoring
11 September 2023, The New Stack

provided by Google News

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

provided by Google News

Vitess, the database clustering system powering YouTube, graduates CNCF incubation
5 November 2019, SiliconANGLE News

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

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

provided by Google News



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