DBMS > Dgraph vs. Google Cloud Bigtable vs. JSqlDb vs. Microsoft Azure SQL Database vs. Snowflake

System Properties Comparison Dgraph vs. Google Cloud Bigtable vs. JSqlDb vs. Microsoft Azure SQL Database vs. Snowflake

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Distributed and scalable native Graph DBMS

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

JavaScript Query Language Database, stores JavaScript objects and primitives

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Primary database model

Graph DBMS

Key-value store
Wide column store

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

dgraph.io

cloud.google.com/bigtable

jsqldb.org (offline)

azure.microsoft.com/en-us/products/azure-sql/database

www.snowflake.com

Technical documentation

dgraph.io/docs

cloud.google.com/bigtable/docs

docs.microsoft.com/en-us/azure/azure-sql

docs.snowflake.net/manuals/index.html

Developer

Dgraph Labs, Inc.

Google

Konrad von Backstrom

Microsoft

Snowflake Computing Inc.

Initial release

2016

2015

2018

2010

2014

Current release

0.8, December 2018

V12

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

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

Linux
OS X
Windows

hosted

Linux
macOS
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

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

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

JavaScript

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

functions in JavaScript

Transact SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Internal replication in Colossus, and regional replication between two clusters in different zones

none

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

yes

In-memory capabilities

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

User concepts

Access control

Planned for future releases

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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

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