DBMS > EJDB vs. Google BigQuery vs. Microsoft Azure Synapse Analytics vs. openGemini vs. Snowflake

System Properties Comparison EJDB vs. Google BigQuery vs. Microsoft Azure Synapse Analytics vs. openGemini vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

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

Primary database model

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

github.com/Softmotions/ejdb

cloud.google.com/bigquery

azure.microsoft.com/services/synapse-analytics

www.opengemini.org
github.com/openGemini

www.snowflake.com

Technical documentation

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

cloud.google.com/bigquery/docs

docs.microsoft.com/azure/synapse-analytics

docs.opengemini.org/guide

docs.snowflake.net/manuals/index.html

Developer

Softmotions

Google

Microsoft

Huawei and openGemini community

Snowflake Computing Inc.

Initial release

2012

2010

2016

2022

2014

Current release

1.1, July 2023

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache Version 2.0

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

hosted

Linux
Windows

hosted

Data scheme

schema-free

yes

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

yes

Integer, Float, Boolean, String

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

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

in-process shared library

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
PHP

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Transact SQL

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

Since BigQuery is designed for querying 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

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

Administrators and common users accounts

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

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