DBMS > FeatureBase vs. LokiJS vs. Microsoft SQL Server vs. SurrealDB

System Properties Comparison FeatureBase vs. LokiJS vs. Microsoft SQL Server vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

In-memory JavaScript DBMS

Microsofts flagship relational DBMS

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Document store
Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

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

Website

www.featurebase.com

github.com/techfort/LokiJS

www.microsoft.com/en-us/sql-server

surrealdb.com

Technical documentation

docs.featurebase.com

techfort.github.io/LokiJS

learn.microsoft.com/en-US/sql/sql-server

surrealdb.com/docs

Developer

Molecula and Pilosa Open Source Contributors

Microsoft

SurrealDB Ltd

Initial release

2017

2014

1989

2022

Current release

2022, May 2022

SQL Server 2022, November 2022

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Open Source

commercial

restricted free version is available

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C++

Rust

Server operating systems

Linux
macOS

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

Linux
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

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

via views

yes

SQL

Support of SQL

SQL queries

yes

SQL-like query language

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

JavaScript API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

Java
Python

JavaScript

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

View functions in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

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