DBMS > LokiJS vs. Microsoft Azure Cosmos DB vs. RisingWave vs. Sadas Engine vs. Teradata Aster

System Properties Comparison LokiJS vs. Microsoft Azure Cosmos DB vs. RisingWave vs. Sadas Engine vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

In-memory JavaScript DBMS

Globally distributed, horizontally scalable, multi-model database service

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

github.com/techfort/LokiJS

azure.microsoft.com/services/cosmos-db

www.risingwave.com/database

www.sadasengine.com

Technical documentation

techfort.github.io/LokiJS

learn.microsoft.com/azure/cosmos-db

docs.risingwave.com/docs/current/intro

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Microsoft

RisingWave Labs

SADAS s.r.l.

Teradata

Initial release

2014

2022

2006

2005

Current release

1.2, September 2023

8.0

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache Version 2.0

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

yes

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)

hosted

Docker
Linux
macOS

AIX
Linux
Windows

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

JSON types

Standard SQL-types and JSON

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

in Aster File Store

Secondary indexes

yes

via views

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JavaScript API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
PostgreSQL wire protocol

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

JavaScript

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

View functions in JavaScript

JavaScript

UDFs in Python or Java

R packages

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

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

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights can be defined down to the item level

Users and Roles

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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