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DBMS > Google Cloud Bigtable vs. Sadas Engine vs. TimescaleDB vs. ToroDB

System Properties Comparison Google Cloud Bigtable vs. Sadas Engine vs. TimescaleDB vs. ToroDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonSadas Engine  Xexclude from comparisonTimescaleDB  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded 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.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelKey-value store
Wide column store
Relational DBMSTime Series DBMSDocument store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.00
Rank#385  Overall
#159  Relational DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websitecloud.google.com/­bigtablewww.sadasengine.comwww.timescale.comgithub.com/­torodb/­server
Technical documentationcloud.google.com/­bigtable/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.timescale.com
DeveloperGoogleSADAS s.r.l.Timescale8Kdata
Initial release2015200620172016
Current release8.02.15.0, May 2024
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen Source infoApache 2.0Open Source infoAGPL-V3
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 languageC++CJava
Server operating systemshostedAIX
Linux
Windows
Linux
OS X
Windows
All OS with a Java 7 VM
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes infostring, integer, double, boolean, date, object_id
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.nonoyesno
Secondary indexesnoyesyes
SQL infoSupport of SQLnoyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesnoneSource-replica replication with hot standby and reads on replicas infoSource-replica replication
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 ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users and roles

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More resources
Google Cloud BigtableSadas EngineTimescaleDBToroDB
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Google Cloud adds graph processing to Spanner, SQL support to Bigtable
1 August 2024, InfoWorld

Google introduces Bigtable SQL access and Spanner's new AI-ready features
1 August 2024, ZDNet

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

PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions
11 June 2024, PR Newswire

Understanding Hyperfunctions in TimescaleDB
11 August 2021, CDOTrends

provided by Google News



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