DBMS > Lovefield vs. SQLite vs. SurrealDB vs. TDSQL for MySQL

System Properties Comparison Lovefield vs. SQLite vs. SurrealDB vs. TDSQL for MySQL

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Widely used embeddable, in-process RDBMS

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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Relational DBMS

Document store
Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	1.11
Rank	#174	Overall
	#30	Document stores
	#17	Graph DBMS

Score	0.96
Rank	#192	Overall
	#88	Relational DBMS

Website

google.github.io/lovefield

www.sqlite.org

surrealdb.com

www.tencentcloud.com/products/dcdb

Technical documentation

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

www.sqlite.org/docs.html

surrealdb.com/docs

www.tencentcloud.com/document/product/1042

Developer

Google

Dwayne Richard Hipp

SurrealDB Ltd

Tencent

Initial release

2014

2000

2022

2013

Current release

2.1.12, February 2017

3.46.1 (13 August 2024), August 2024

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

commercial

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

JavaScript

Rust

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

server-less

Linux
macOS
Windows

hosted

Data scheme

yes

dynamic column types

schema-free

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

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

SQL-like query language

yes

APIs and other access methods

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL
RESTful HTTP API
WebSocket

JDBC
ODBC

Supported programming languages

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

Deno
Go
JavaScript (Node.js)
Rust

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

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

yes, based on authentication and database rules

Users with fine-grained authorization concept

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