DBMS > GeoSpock vs. HarperDB vs. LokiJS vs. Microsoft Azure Cosmos DB vs. Sadas Engine

System Properties Comparison GeoSpock vs. HarperDB vs. LokiJS vs. Microsoft Azure Cosmos DB vs. Sadas Engine

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

In-memory JavaScript DBMS

Globally distributed, horizontally scalable, multi-model database service

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

Primary database model

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	0.60
Rank	#244	Overall
	#38	Document stores

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	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

geospock.com

www.harperdb.io

github.com/techfort/LokiJS

azure.microsoft.com/services/cosmos-db

www.sadasengine.com

Technical documentation

docs.harperdb.io/docs

techfort.github.io/LokiJS

learn.microsoft.com/azure/cosmos-db

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

Developer

GeoSpock

HarperDB

Microsoft

SADAS s.r.l.

Initial release

2017

2014

2006

Current release

2.0, September 2019

3.1, August 2021

8.0

License

Commercial or Open Source

commercial

free community edition available

Open Source

commercial

free trial version available

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

Java, Javascript

Node.js

JavaScript

C++

Server operating systems

hosted

Linux
OS X

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

hosted

AIX
Linux
Windows

Data scheme

yes

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

yes

JSON types

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

temporal, categorical

yes

via views

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like data manipulation statements

SQL-like query language

yes

APIs and other access methods

JDBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JavaScript API

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

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

JavaScript

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

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

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

View functions in JavaScript

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

none

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

atomic operations within a single collection possible

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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 for users can be defined per table

Access rights for users and roles

Access rights can be defined down to the item level

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

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