DBMS > Google BigQuery vs. HugeGraph vs. Microsoft Access vs. OpenSearch

System Properties Comparison Google BigQuery vs. HugeGraph vs. Microsoft Access vs. OpenSearch

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A fast-speed and highly-scalable Graph DBMS

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Primary database model

Secondary database models

Vector DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Website

cloud.google.com/bigquery

github.com/hugegraph
hugegraph.apache.org

www.microsoft.com/en-us/microsoft-365/access

github.com/opensearch-project
opensearch.org

Technical documentation

cloud.google.com/bigquery/docs

hugegraph.apache.org/docs

developer.microsoft.com/en-us/access

opensearch.org/docs/latest

Developer

Google

Baidu

Microsoft

Amazon Web Services

Initial release

2010

2018

1992

2021

Current release

0.9

1902 (16.0.11328.20222), March 2019

2.5.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Bundled with Microsoft Office

Open Source

Apache Version 2.0

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.

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Implementation language

Java

C++

Java

Server operating systems

hosted

Linux
macOS
Unix

Windows

Not a real database server, but making use of DLLs

All OS with a Java VM

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

also supports composite index and range index

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
DAO
ODBC
OLE DB

Java API
RESTful HTTP/JSON API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Groovy
Java
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

user defined functions

in JavaScript

asynchronous Gremlin script jobs

yes

since Access 2010 using the ACE-engine

yes

Triggers

yes

since Access 2010 using the ACE-engine

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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)

Users, roles and permissions

a simple user-level security was built in till version Access 2003

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
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Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
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Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
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