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 DynamoDB vs. Prometheus vs. TDengine vs. Warp 10

System Properties Comparison Amazon DynamoDB vs. Prometheus vs. TDengine vs. Warp 10

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonPrometheus  Xexclude from comparisonTDengine  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudOpen-source Time Series DBMS and monitoring systemTime Series DBMS and big data platformTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument store
Key-value store
Time Series DBMSTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.07
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websiteaws.amazon.com/­dynamodbprometheus.iogithub.com/­taosdata/­TDengine
tdengine.com
www.warp10.io
Technical documentationdocs.aws.amazon.com/­dynamodbprometheus.io/­docsdocs.tdengine.comwww.warp10.io/­content/­02_Getting_started
DeveloperAmazonTDEngine, previously Taos DataSenX
Initial release2012201520192015
Current release3.0, August 2022
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache 2.0Open Source infoAGPL V3, also commercial editions availableOpen Source infoApache License 2.0
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 languageGoCJava
Server operating systemshostedLinux
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-free
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.no infoImport of XML data possiblenono
Secondary indexesyesnonono
SQL infoSupport of SQLnonoStandard SQL with extensions for time-series applicationsno
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON APIJDBC
RESTful HTTP API
HTTP API
Jupyter
WebSocket
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnononoyes infoWarpScript
Triggersyes infoby integration with AWS Lambdanoyes, via alarm monitoringno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby Federationyesselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
noneImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionnono
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
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noyesMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
Amazon DynamoDBPrometheusTDengineWarp 10
Specific characteristicsTDengine™ 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

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

TDengine 3.3.0.0 Release Notes
7 May 2024

How to Unlock Value from Industrial Data with AI and ML Technology
6 May 2024

Compare InfluxDB vs. TDengine
19 April 2024

Why We Need the Next Generation Data Historian
15 April 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
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

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

More resources
Amazon DynamoDBPrometheusTDengineWarp 10
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Increased popularity for consuming DBMS services out of the cloud
2 October 2015, Paul Andlinger

show all

Recent citations in the news

How Heroku reduced their operational overhead by migrating their 30 TB self-managed database from Amazon EC2 to ...
9 May 2024, AWS Blog

Using Elasticsearch to Offload Search and Analytics from DynamoDB: Pros and Cons
10 May 2024, hackernoon.com

Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services
20 March 2024, AWS Blog

Bulk update Amazon DynamoDB tables with AWS Step Functions | Amazon Web Services
20 March 2024, AWS Blog

A new and improved AWS CDK construct for Amazon DynamoDB tables | Amazon Web Services
31 January 2024, AWS Blog

provided by Google News

VTEX scales to 150 million metrics using Amazon Managed Service for Prometheus | Amazon Web Services
10 March 2024, AWS Blog

VictoriaMetrics Offers Prometheus Replacement for Time Series Monitoring
17 July 2023, The New Stack

Linux System Monitoring with Prometheus, Grafana, and collectd
1 February 2024, Linux Journal

How to reduce Istio sidecar metric cardinality with Amazon Managed Service for Prometheus | Amazon Web Services
10 October 2023, AWS Blog

Consider Grafana vs. Prometheus for your time-series tools
18 October 2021, TechTarget

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

provided by Google News

Time Series Intelligence Software Market Business Insights, Key Trend Analysis | Google, SAP, Azure Time Series ...
24 April 2024, Amoré

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

RaimaDB logo

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

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
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

Neo4j logo

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

Present your product here