DBMS > Apache Phoenix vs. openGemini vs. RDF4J vs. TiDB

System Properties Comparison Apache Phoenix vs. openGemini vs. RDF4J vs. TiDB

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Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

Secondary database models

Document store

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	4.09
Rank	#72	Overall
	#38	Relational DBMS

Website

phoenix.apache.org

www.opengemini.org
github.com/openGemini

rdf4j.org

pingcap.com

Technical documentation

phoenix.apache.org

docs.opengemini.org/guide

rdf4j.org/documentation

docs.pingcap.com/tidb/stable

Developer

Apache Software Foundation

Huawei and openGemini community

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

PingCAP, Inc.

Initial release

2014

2022

2004

2016

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

1.1, July 2023

8.2.0, July 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Go, Rust

Server operating systems

Linux
Unix
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

yes

SQL-like query language

yes

APIs and other access methods

JDBC

HTTP REST

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

GORM
JDBC
ODBC
Proprietary protocol
SQLAlchemy

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

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

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by key range)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

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

Hadoop integration

yes

with TiSpark Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

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

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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 Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Administrators and common users accounts

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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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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