DBMS > GeoSpock vs. Lovefield vs. MySQL vs. SurrealDB

System Properties Comparison GeoSpock vs. Lovefield vs. MySQL vs. SurrealDB

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store
Graph DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

geospock.com

google.github.io/lovefield

www.mysql.com

surrealdb.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

dev.mysql.com/doc

surrealdb.com/docs

Developer

GeoSpock

Google

Oracle

since 2010, originally MySQL AB, then Sun

SurrealDB Ltd

Initial release

2014

1995

2022

Current release

2.0, September 2019

2.1.12, February 2017

8.4.0, April 2024

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java, Javascript

JavaScript

C and C++

Rust

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

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.

yes

Secondary indexes

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC
Proprietary native API

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

JavaScript

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

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

Access rights for users can be defined per table

Users with fine-grained authorization concept

no user groups or roles

yes, based on authentication and database rules

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