DBMS > GeoMesa vs. SQream DB vs. ToroDB vs. Vitess

System Properties Comparison GeoMesa vs. SQream DB vs. ToroDB vs. Vitess

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

a GPU-based, columnar RDBMS for big data analytics workloads

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

www.geomesa.org

sqream.com

github.com/torodb/server

vitess.io

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

docs.sqream.com

vitess.io/docs

Developer

CCRi and others

SQream Technologies

8Kdata

The Linux Foundation, PlanetScale

Initial release

2014

2017

2016

2013

Current release

5.0.0, May 2024

2022.1.6, December 2022

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

AGPL-V3

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

C++, CUDA, Haskell, Java, Scala

Java

Server operating systems

Linux

All OS with a Java 7 VM

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

string, integer, double, boolean, date, object_id

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

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

.Net
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

depending on storage layer

horizontal and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

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

table locks or row locks depending on storage engine

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

I SQream, you SQream, we all SQream for … data analytics?
5 October 2023, Fierce Network

SQream Announces Strategic Integration for Powerful Big Data Analytics with Dataiku
9 February 2024, insideBIGDATA

SQream Joins Samsung Cloud Platform Ecosystem
26 July 2023, Datanami

GPU data warehouse startup SQream lands $39.4M funding round
24 June 2020, SiliconANGLE News

SQream Technologies raises $39.4 million for GPU-accelerated databases
24 June 2020, VentureBeat

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube — now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News

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