DBMS > Amazon Redshift vs. SingleStore vs. SpatiaLite vs. Vitess

System Properties Comparison Amazon Redshift vs. SingleStore vs. SpatiaLite vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Spatial extension of SQLite

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

Relational DBMS

Document store
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

aws.amazon.com/redshift

www.singlestore.com

www.gaia-gis.it/fossil/libspatialite/index

vitess.io

Technical documentation

docs.aws.amazon.com/redshift

docs.singlestore.com

www.gaia-gis.it/gaia-sins/spatialite_topics.html

vitess.io/docs

Developer

Amazon (based on PostgreSQL)

SingleStore Inc.

Alessandro Furieri

The Linux Foundation, PlanetScale

Initial release

2012

2013

2008

2013

Current release

8.5, January 2024

5.0.0, August 2020

15.0.2, December 2022

License

Commercial or Open Source

commercial

free developer edition available

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

Apache Version 2.0, commercial licenses available

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C++, Go

C++

Server operating systems

hosted

Linux

64 bit version required

server-less

Docker
Linux
macOS

Data scheme

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

but no triggers and foreign keys

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Bash
C
C#
Java
JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

hash partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Fine grained access control via users, groups and roles

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
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Competitive advantages

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Typical application scenarios

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Key customers

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
» more

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