DBMS > Amazon DynamoDB vs. Atos Standard Common Repository vs. CrateDB vs. Fauna vs. TDengine

System Properties Comparison Amazon DynamoDB vs. Atos Standard Common Repository vs. CrateDB vs. Fauna vs. TDengine

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

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

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Distributed Database based on Lucene

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Time Series DBMS and big data platform

Primary database model

Document store
Key-value store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

aws.amazon.com/dynamodb

atos.net/en/convergence-creators/portfolio/standard-common-repository

cratedb.com

fauna.com

github.com/taosdata/TDengine
tdengine.com

Technical documentation

docs.aws.amazon.com/dynamodb

cratedb.com/docs

docs.fauna.com

docs.tdengine.com

Developer

Amazon

Atos Convergence Creators

Crate

Fauna, Inc.

TDEngine, previously Taos Data

Initial release

2012

2016

2013

2014

2019

Current release

1703

3.0, August 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

commercial

Open Source

AGPL V3, also commercial editions available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Implementation language

Java

Scala

Server operating systems

hosted

Linux

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Linux
Windows

Data scheme

schema-free

Schema and schema-less with LDAP views

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

Standard SQL with extensions for time-series applications

APIs and other access methods

RESTful HTTP API

LDAP

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

RESTful HTTP API

JDBC
RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages with LDAP bindings

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

Server-side scripts

Stored procedures

user defined functions (Javascript)

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

horizontal partitioning

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Configurable replication on table/partition-level

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

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

Atomic execution of specific operations

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

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

LDAP bind authentication

rights management via user accounts

Identity management, authentication, and access control

yes

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
» more

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

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more

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

Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more

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

Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
» more

Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more

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

Licensing and pricing models

See CrateDB pricing >
» more

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

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22 May 2024

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