DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon DocumentDB vs. Google Cloud Bigtable vs. Graphite vs. TDengine

System Properties Comparison Amazon DocumentDB vs. Google Cloud Bigtable vs. Graphite vs. TDengine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGraphite  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperTime Series DBMS and big data platform
Primary database modelDocument storeKey-value store
Wide column store
Time Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­bigtablegithub.com/­graphite-project/­graphite-webgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­bigtable/­docsgraphite.readthedocs.iodocs.tdengine.com
DeveloperGoogleChris DavisTDEngine, previously Taos Data
Initial release2019201520062019
Current release3.0, August 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC
Server operating systemshostedhostedLinux
Unix
Linux
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoNumeric data onlyyes
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.nononono
Secondary indexesyesnonono
SQL infoSupport of SQLnononoStandard SQL with extensions for time-series applications
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Sockets
JDBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript (Node.js)
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnononono
Triggersnononoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasInternal replication in Colossus, and regional replication between two clusters in different zonesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)none
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infolockingyes
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.no
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes
More information provided by the system vendor
Amazon DocumentDBGoogle Cloud BigtableGraphiteTDengine
Specific characteristicsTDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
News

Seamless Data Integration from MQTT and InfluxDB to TDengine
22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

What Is Predictive Maintenance?
17 May 2024

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon DocumentDBGoogle Cloud BigtableGraphiteTDengine
DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot | Amazon Web Services
20 May 2024, AWS Blog

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces Amazon DocumentDB I/O-Optimized
21 November 2023, AWS Blog

AWS announces vector search for Amazon DocumentDB
29 November 2023, AWS Blog

Use headless clusters in Amazon DocumentDB for cost-effective multi-Region resiliency | Amazon Web Services
8 March 2024, AWS Blog

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

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

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

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

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

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

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

How Grafana made observability accessible
12 June 2023, InfoWorld

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

provided by Google News

TDengine named Top Global Industrial Data Management Solution
4 January 2024, IT Brief Australia

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

TDengine debuts cloud-based time-series data processing platform for IoT deployments
20 September 2022, SiliconANGLE News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MindsDB is now the leading and fastest growing applied ML platform in the world India - English
3 November 2022, PR Newswire

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here