DBMS > Google BigQuery vs. Microsoft Azure Synapse Analytics vs. Oracle Coherence vs. TigerGraph

System Properties Comparison Google BigQuery vs. Microsoft Azure Synapse Analytics vs. Oracle Coherence vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

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

Oracles in-memory data grid solution

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Key-value store

Graph DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

cloud.google.com/bigquery

azure.microsoft.com/services/synapse-analytics

www.oracle.com/java/coherence

www.tigergraph.com

Technical documentation

cloud.google.com/bigquery/docs

docs.microsoft.com/azure/synapse-analytics

docs.oracle.com/en/middleware/standalone/coherence

docs.tigergraph.com

Developer

Google

Microsoft

Oracle

Initial release

2010

2016

2007

2017

Current release

14.1, August 2023

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

hosted

All OS with a Java VM

Linux

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

JCache
JPA
RESTful HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
PHP

.Net
C++
Java

C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Transact SQL

yes

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

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

yes

Relationships in graphs

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

Role-based access control

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