DBMS > Amazon Redshift vs. BigObject vs. YugabyteDB

System Properties Comparison Amazon Redshift vs. BigObject vs. YugabyteDB

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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

High-performance distributed SQL database for global, internet-scale applications. Wire compatible with PostgreSQL.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Document store
Wide column store

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Score	22.42
Rank	#33	Overall
	#19	Relational DBMS

Score	0.08
Rank	#308	Overall
	#135	Relational DBMS

Score	0.92
Rank	#179	Overall
	#90	Relational DBMS

Website

aws.amazon.com/redshift

bigobject.io

www.yugabyte.com

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Yugabyte Inc.

Initial release

2012

2015

2017

Current release

2.4, January 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

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

C and 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
OS X

Data scheme

yes

depending on used data model

Typing

predefined data types such as float or date

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes, PostgreSQL compatible

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language

Supported programming languages

All languages supporting JDBC/ODBC

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

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

yes

sql, plpgsql, C

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Hash and Range Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

based on RocksDB

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

yes

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