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DBMS > Google Cloud Bigtable vs. Graph Engine vs. openGemini vs. TimescaleDB

System Properties Comparison Google Cloud Bigtable vs. Graph Engine vs. openGemini vs. TimescaleDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonopenGemini  Xexclude from comparisonTimescaleDB  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.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineAn open source distributed Time Series DBMS with high concurrency, high performance, and high scalabilityA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value store
Wide column store
Graph DBMS
Key-value store
Time Series DBMSTime Series DBMS
Secondary database modelsRelational 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
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score0.09
Rank#361  Overall
#37  Time Series DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitecloud.google.com/­bigtablewww.graphengine.iowww.opengemini.org
github.com/­openGemini
www.timescale.com
Technical documentationcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualdocs.opengemini.org/­guidedocs.timescale.com
DeveloperGoogleMicrosoftHuawei and openGemini communityTimescale
Initial release2015201020222017
Current release1.1, July 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CGoC
Server operating systemshosted.NETLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesInteger, Float, Boolean, Stringnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesnoyesyes
SQL infoSupport of SQLnonoSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIHTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
F#
Visual Basic
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Administrators and common users accountsfine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableGraph Engine infoformer name: TrinityopenGeminiTimescaleDB
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 Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

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

provided by Google News

Trinity
30 October 2010, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

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About HUAWEI Open Source
9 February 2022, Huawei

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News



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