DBMS > Amazon Redshift vs. GreptimeDB vs. SQLite vs. Transbase vs. VoltDB

System Properties Comparison Amazon Redshift vs. GreptimeDB vs. SQLite vs. Transbase vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Widely used embeddable, in-process RDBMS

A resource-optimized, high-performance, universally applicable RDBMS

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

aws.amazon.com/redshift

greptime.com

www.sqlite.org

www.transaction.de/en/products/transbase.html

www.voltdb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.greptime.com

www.sqlite.org/docs.html

www.transaction.de/en/products/transbase/features.html

docs.voltdb.com

Developer

Amazon (based on PostgreSQL)

Greptime Inc.

Dwayne Richard Hipp

Transaction Software GmbH

VoltDB Inc.

Initial release

2012

2022

2000

1987

2010

Current release

3.46.1 (13 August 2024), August 2024

Transbase 8.3, 2022

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Public Domain

commercial

free development license

Open Source

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

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

Rust

C and C++

Java, C++

Server operating systems

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

server-less

FreeBSD
Linux
macOS
Solaris
Windows

Linux
OS X

for development

Data scheme

yes

schema-free, schema definition possible

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

gRPC
HTTP API
JDBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C++
Erlang
Go
Java
JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Python

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Simple rights management via user accounts

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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