DBMS > EJDB vs. Prometheus vs. Sadas Engine vs. Snowflake

System Properties Comparison EJDB vs. Prometheus vs. Sadas Engine vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Open-source Time Series DBMS and monitoring system

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store

Time Series DBMS

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

github.com/Softmotions/ejdb

prometheus.io

www.sadasengine.com

www.snowflake.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

prometheus.io/docs

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

docs.snowflake.net/manuals/index.html

Developer

Softmotions

SADAS s.r.l.

Snowflake Computing Inc.

Initial release

2012

2015

2006

2014

Current release

8.0

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache 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

C++

Server operating systems

server-less

Linux
Windows

AIX
Linux
Windows

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

Numeric data only

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.

Import of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol

CLI Client
JDBC
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by Federation

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

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, groups and roles according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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