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DBMS > Google Cloud Bigtable vs. GridGain vs. TDengine

System Properties Comparison Google Cloud Bigtable vs. GridGain vs. TDengine

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonTDengine  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.GridGain is an in-memory computing platform, built on Apache IgniteTime Series DBMS and big data platform
Primary database modelKey-value store
Wide column store
Columnar
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.67
Rank#95  Overall
#15  Key-value stores
#6  Wide column stores
Score1.32
Rank#156  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#70  Relational DBMS
Score1.76
Rank#127  Overall
#10  Time Series DBMS
Websitecloud.google.com/­bigtablewww.gridgain.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationcloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmldocs.tdengine.com
DeveloperGoogleGridGain Systems, Inc.TDEngine, previously Taos Data
Initial release201520072019
Current releaseGridGain 8.5.13.0, August 2022
License infoCommercial or Open Sourcecommercialcommercial, open sourceOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .Net, Python, REST, SQLC
Server operating systemshostedLinux
OS X
Solaris
Windows
z/OS
Linux
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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 SQLnoANSI-99 for query and DML statements, subset of DDLStandard SQL with extensions for time-series applications
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes (cache interceptors and events)yes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control
Security Hooks for custom implementations
yes
More information provided by the system vendor
Google Cloud BigtableGridGainTDengine
Specific characteristicsTDengine™ is a time-series database designed to help traditional industries overcome...
» more
Competitive advantagesHigh Performance at Any Scale: With its distributed scalable architecture that grows...
» more
Typical application scenariosTDengine is purpose-built for Industry 4.0 and the Industrial IoT (IIoT) and particularly...
» more
Market metricsTDengine has garnered over 23,000 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is free, open-source software released under the AGPLv3. TDengine Enterprise...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Google Cloud BigtableGridGainTDengine
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1 August 2024, TechCrunch

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

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

Google Launches Bigtable, A Big Managed Database In The Cloud
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22 January 2025, PR Newswire

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24 February 2025, Yahoo Finance

GridGain Advances Its Unified Real-Time Data Platform to Help Enterprises Accelerate AI-Driven Data Processing
10 July 2024, insideAI News

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4 February 2025, PR Newswire

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Revolutionizing Success in the Time Series Database(TSDB)
7 March 2025, openPR

TDengine Brings Open Source Time-Series Database to Kubernetes
23 August 2022, Cloud Native Now

New TDengine Benchmark Results Show Up to 37.0x Higher Query Performance Than InfluxDB and TimescaleDB
28 February 2023, GlobeNewswire

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