DBMS > Datomic vs. Lovefield vs. SurrealDB vs. Transbase

System Properties Comparison Datomic vs. Lovefield vs. SurrealDB vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable relational database for web apps written in pure JavaScript

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

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

Primary database model

Relational DBMS

Document store
Graph DBMS

Relational DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

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

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

www.datomic.com

google.github.io/lovefield

surrealdb.com

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

Technical documentation

docs.datomic.com

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

surrealdb.com/docs

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

Developer

Cognitect

Google

SurrealDB Ltd

Transaction Software GmbH

Initial release

2012

2014

2022

1987

Current release

1.0.7075, December 2023

2.1.12, February 2017

v1.5.0, May 2024

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

Open Source

commercial

free development license

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

Java, Clojure

JavaScript

Rust

C and C++

Server operating systems

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

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

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

GraphQL
RESTful HTTP API
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Clojure
Java

JavaScript

Deno
Go
JavaScript (Node.js)
Rust

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

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

By using transaction functions

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

using MemoryDB

User concepts

Access control

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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