DBMS > Lovefield vs. Splunk vs. SurrealDB vs. Tkrzw

System Properties Comparison Lovefield vs. Splunk vs. SurrealDB vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Analytics Platform for Big Data

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Search engine

Document store
Graph DBMS

Key-value store

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

google.github.io/lovefield

www.splunk.com

surrealdb.com

dbmx.net/tkrzw

Technical documentation

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

docs.splunk.com/Documentation/Splunk

surrealdb.com/docs

Developer

Google

Splunk Inc.

SurrealDB Ltd

Mikio Hirabayashi

Initial release

2014

2003

2022

2020

Current release

2.1.12, February 2017

v1.1.1, January 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

Open Source

Apache Version 2.0

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

JavaScript

Rust

C++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux
macOS

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

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

Splunk Search Processing Language for search commands

SQL-like query language

APIs and other access methods

HTTP REST

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

JavaScript

C#
Java
JavaScript
PHP
Python
Ruby

Deno
Go
JavaScript (Node.js)
Rust

C++
Java
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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

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

using specific database classes

User concepts

Access control

Access rights for users and roles

yes, based on authentication and database rules

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More resources

DB-Engines blog posts

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