DBMS > Amazon Redshift vs. Firebolt vs. Graph Engine vs. OpenTSDB vs. TerarkDB

System Properties Comparison Amazon Redshift vs. Firebolt vs. Graph Engine vs. OpenTSDB vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Scalable Time Series DBMS based on HBase

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Time Series DBMS

Key-value store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.90
Rank	#134	Overall
	#62	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

aws.amazon.com/redshift

www.firebolt.io

www.graphengine.io

opentsdb.net

github.com/bytedance/terarkdb

Technical documentation

docs.aws.amazon.com/redshift

docs.firebolt.io

www.graphengine.io/docs/manual

opentsdb.net/docs/build/html/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Amazon (based on PostgreSQL)

Firebolt Analytics Inc.

Microsoft

currently maintained by Yahoo and other contributors

ByteDance, originally Terark

Initial release

2012

2020

2010

2011

2016

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

LGPL

commercial

restricted open source version 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.

Implementation language

.NET and C

Java

C++

Server operating systems

hosted

.NET

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

.Net
ODBC
RESTful HTTP API

RESTful HTTP API

HTTP API
Telnet API

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

Go
JavaScript (Node.js)
Python

C#
C++
F#
Visual Basic

Erlang
Go
Java
Python
R
Ruby

C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

fine grained access rights according to SQL-standard

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