DBMS > Apache IoTDB vs. Dgraph vs. Sadas Engine vs. TiDB

System Properties Comparison Apache IoTDB vs. Dgraph vs. Sadas Engine vs. TiDB

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Distributed and scalable native Graph DBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

TiDB is an open source distributed SQL database that supports Hybrid Transactional/Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Primary database model

Time Series DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	4.09
Rank	#72	Overall
	#38	Relational DBMS

Website

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

dgraph.io/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.pingcap.com/tidb/stable

Developer

Apache Software Foundation

Dgraph Labs, Inc.

SADAS s.r.l.

PingCAP, Inc.

Initial release

2018

2016

2006

2016

Current release

1.1.0, April 2023

8.0

8.2.0, July 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

free trial version available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

TiDB Cloud: Fully-managed TiDB Service. Bring everything great about TiDB to the cloud.

Implementation language

Java

C++

Go, Rust

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

AIX
Linux
Windows

Linux

Data scheme

yes

schema-free

yes

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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JDBC
ODBC
Proprietary protocol

GORM
JDBC
ODBC
Proprietary protocol
SQLAlchemy

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

yes

horizontal partitioning

horizontal partitioning (by key range)

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Synchronous replication via Raft

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

with TiSpark Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

full support since version 6.6

Transaction concepts

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

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

managed by 'Learn by Usage'

User concepts

Access control

yes

Planned for future releases

Access rights for users, groups and roles according to SQL-standard

Fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

TiDB is an advanced open-source, distributed SQL database for modern application...
» more

Competitive advantages

- HORIZONTAL SCALING : TiDB grants total transparency into your data workloads without...
» more

Typical application scenarios

TiDB is ideal for transactional applications that require extreme scalability and...
» more

Key customers

Block, Pinterest, Catalyst, Bolt, Flipkart, Capcom, Shopee (E-commerce), JD Cloud...
» more

Market metrics

34K+ GitHub stars 5K+ members in TiDB Community Slack 1K+ community contributors...
» more

Licensing and pricing models

TiDB Community : Free open source software (Apache 2.0) TiDB Self-Hosted : 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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