DBMS > LokiJS vs. Microsoft Access vs. Oracle vs. Oracle NoSQL vs. QuestDB

System Properties Comparison LokiJS vs. Microsoft Access vs. Oracle vs. Oracle NoSQL vs. QuestDB

Editorial information provided by DB-Engines

Name

Description

In-memory JavaScript DBMS

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used RDBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A high performance open source SQL database for time series data

Primary database model

Document store

Relational DBMS

Document store
Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Relational DBMS

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

Score	0.48
Rank	#262	Overall
	#42	Document stores

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Score	2.48
Rank	#115	Overall
	#9	Time Series DBMS

Website

github.com/techfort/LokiJS

www.microsoft.com/en-us/microsoft-365/access

www.oracle.com/database

www.oracle.com/database/nosql/technologies/nosql

questdb.io

Technical documentation

techfort.github.io/LokiJS

developer.microsoft.com/en-us/access

docs.oracle.com/en/database

docs.oracle.com/en/database/other-databases/nosql-database/index.html

questdb.io/docs

Developer

Microsoft

Oracle

QuestDB Technology Inc

Initial release

2014

1992

1980

2011

2014

Current release

1902 (16.0.11328.20222), March 2019

23c, September 2023

23.3, December 2023

License

Commercial or Open Source

Open Source

commercial

Bundled with Microsoft Office

commercial

restricted free version is available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Apache 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

C++

C and C++

Java

Java (Zero-GC), C++, Rust

Server operating systems

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

Windows

Not a real database server, but making use of DLLs

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
Solaris SPARC/x86

Linux
macOS
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes

optional

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

yes

but not compliant to any SQL standard

yes

with proprietary extensions

SQL-like DML and DDL statements

SQL with time-series extensions

APIs and other access methods

JavaScript API

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

JavaScript

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C
C#
Go
Java
JavaScript (Node.js)
Python

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

View functions in JavaScript

yes

since Access 2010 using the ACE-engine

PL/SQL

also stored procedures in Java possible

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single collection possible

ACID

but no files for transaction logging

ACID

isolation level can be parameterized

configurable

ACID within a storage node (=shard)

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

but no files for transaction logging

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

off heap cache

yes

through memory mapped files

User concepts

Access control

a simple user-level security was built in till version Access 2003

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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