DBMS > Amazon Redshift vs. BoltDB vs. H2 vs. ReductStore

System Properties Comparison Amazon Redshift vs. BoltDB vs. H2 vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Secondary database models

Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

aws.amazon.com/redshift

github.com/boltdb/bolt

www.h2database.com

github.com/reductstore
www.reduct.store

Technical documentation

docs.aws.amazon.com/redshift

www.h2database.com/html/main.html

www.reduct.store/docs

Developer

Amazon (based on PostgreSQL)

Thomas Mueller

ReductStore LLC

Initial release

2012

2013

2005

2023

Current release

2.2.220, July 2023

1.9, March 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Business Source License 1.1

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

C++, Rust

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

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

yes

APIs and other access methods

JDBC
ODBC

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

fine grained access rights according to SQL-standard

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