DBMS > Amazon DynamoDB vs. Heroic vs. LokiJS vs. Microsoft Access vs. Sqrrl

System Properties Comparison Amazon DynamoDB vs. Heroic vs. LokiJS vs. Microsoft Access vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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.)

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Key-value store

Time Series DBMS

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.48
Rank	#262	Overall
	#42	Document stores

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Website

aws.amazon.com/dynamodb

github.com/spotify/heroic

github.com/techfort/LokiJS

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

sqrrl.com

Technical documentation

docs.aws.amazon.com/dynamodb

spotify.github.io/heroic

techfort.github.io/LokiJS

developer.microsoft.com/en-us/access

Developer

Amazon

Spotify

Microsoft

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2014

1992

2012

Current release

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

Open Source

commercial

Bundled with Microsoft Office

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

C++

Java

Server operating systems

hosted

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

Windows

Not a real database server, but making use of DLLs

Linux

Data scheme

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.

Secondary indexes

yes

via Elasticsearch

yes

via views

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

APIs and other access methods

RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JavaScript API

ADO.NET
DAO
ODBC
OLE DB

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

JavaScript

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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

View functions in JavaScript

yes

since Access 2010 using the ACE-engine

Triggers

yes

by integration with AWS Lambda

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate Consistency

none

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

atomic operations within a single collection possible

ACID

but no files for transaction logging

Atomic updates per row, document, or graph entity

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

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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