DBMS > Amazon DynamoDB vs. TDengine vs. Vertica vs. YugabyteDB

System Properties Comparison Amazon DynamoDB vs. TDengine vs. Vertica vs. YugabyteDB

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Time Series DBMS and big data platform

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Column oriented

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

Document store
Wide column store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Score	2.91
Rank	#102	Overall
	#51	Relational DBMS

Website

aws.amazon.com/dynamodb

github.com/taosdata/TDengine
tdengine.com

www.vertica.com

www.yugabyte.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.tdengine.com

vertica.com/documentation

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Amazon

TDEngine, previously Taos Data

OpenText

previously Micro Focus and Hewlett Packard

Yugabyte Inc.

Initial release

2012

2019

2005

2017

Current release

3.0, August 2022

12.0.3, January 2023

2.19, September 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL V3, also commercial editions available

commercial

Limited community edition free

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

C++

C and C++

Server operating systems

hosted

Linux
Windows

Linux

Linux
OS X

Data scheme

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

depending on used data model

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

SQL

Support of SQL

Standard SQL with extensions for time-series applications

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

yes, PostgreSQL compatible

APIs and other access methods

RESTful HTTP API

JDBC
RESTful HTTP API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

yes

sql, plpgsql, C

Triggers

yes

by integration with AWS Lambda

yes, via alarm monitoring

yes, called Custom Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, hierarchical partitioning

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

ACID

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

based on RocksDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more

Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
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Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Systems of record and engagement for cloud native applications that require resilience,...
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Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

Cost-based models and subscription-based models are both available. One license is...
» more

Apache 2.0 license for the database
» more

News

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17 May 2024

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.