DBMS > Dgraph vs. Prometheus vs. Sequoiadb vs. TimescaleDB

System Properties Comparison Dgraph vs. Prometheus vs. Sequoiadb vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Open-source Time Series DBMS and monitoring system

NewSQL database with distributed OLTP and SQL

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

Primary database model

Graph DBMS

Time Series DBMS

Document store
Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

Technical documentation

dgraph.io/docs

prometheus.io/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.timescale.com

Developer

Dgraph Labs, Inc.

Sequoiadb Ltd.

Timescale

Initial release

2016

2015

2013

2017

Current release

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Server: AGPL; Client: Apache V2

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.

Implementation language

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

oid, date, timestamp, binary, regex

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

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.

Import of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

RESTful HTTP/JSON API

proprietary protocol using JSON

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

Supported programming languages

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

.Net
C++
Java
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

JavaScript

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

yes

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

by Federation

Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

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.

User concepts

Access control

Planned for future releases

simple password-based access control

fine grained access rights according to SQL-standard

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More resources

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