DBMS > Amazon Redshift vs. BigObject vs. Brytlyt vs. VoltDB vs. XTDB

System Properties Comparison Amazon Redshift vs. BigObject vs. Brytlyt vs. VoltDB vs. XTDB

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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store

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Trend Chart

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

aws.amazon.com/redshift

bigobject.io

brytlyt.io

www.voltdb.com

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

Technical documentation

docs.aws.amazon.com/redshift

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Brytlyt

VoltDB Inc.

Juxt Ltd.

Initial release

2012

2015

2016

2010

2019

Current release

5.0, August 2023

11.3, April 2022

1.19, September 2021

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and CUDA

Java, C++

Clojure

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
Windows

Linux
OS X

for development

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

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

specific XML-type available, but no XML query functionality.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

only a subset of SQL 99

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

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

Java API
JDBC
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

user defined functions

in PL/pgSQL

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

Multi-source replication
Source-replica replication

yes, each node contains all data

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Snapshots and command logging

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

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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