DBMS > Amazon Redshift vs. BigObject vs. QuestDB vs. Rockset

System Properties Comparison Amazon Redshift vs. BigObject vs. QuestDB vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

A high performance open source SQL database for time series data

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Document store

Secondary database models

Relational DBMS

Relational DBMS
Search engine

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

aws.amazon.com/redshift

bigobject.io

questdb.io

rockset.com

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

questdb.io/docs

docs.rockset.com

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

QuestDB Technology Inc

Rockset

Initial release

2012

2015

2014

2019

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

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

Java (Zero-GC), C++, Rust

C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
macOS
Windows

hosted

Data scheme

yes

schema-free via InfluxDB Line Protocol

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

restricted

yes

all fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

SQL with time-series extensions

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

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

over HTTP

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by timestamps)

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication with eventual consistency

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

through memory mapped files

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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