DBMS > BigObject vs. Dgraph vs. TiDB vs. TimescaleDB vs. XTDB

System Properties Comparison BigObject vs. Dgraph vs. TiDB vs. TimescaleDB vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Distributed and scalable native Graph DBMS

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.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Document store

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	4.66
Rank	#70	Overall
	#38	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.bigobject.io

dgraph.io/docs

docs.pingcap.com/tidb/stable

docs.timescale.com

www.xtdb.com/docs

Developer

BigObject, Inc.

Dgraph Labs, Inc.

PingCAP, Inc.

Timescale

Juxt Ltd.

Initial release

2015

2016

2017

2019

Current release

8.0.0, March 2024

2.15.0, May 2024

1.19, September 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

MIT License

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

Go, Rust

Clojure

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

Linux

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

yes, extensible-data-notation format

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

SQL-like DML and DDL statements

yes

full PostgreSQL SQL syntax

limited SQL, making use of Apache Calcite

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

GORM
JDBC
ODBC
Proprietary protocol
SQLAlchemy

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST
JDBC

Supported programming languages

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

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Clojure
Java

Server-side scripts

Stored procedures

Lua

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal partitioning (by key range)

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication via Raft

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

Source-replica replication with hot standby and reads on replicas

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with TiSpark Connector

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

full support since version 6.6

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

Planned for future releases

Fine grained access rights 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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