DBMS > Google Cloud Datastore vs. Microsoft Access vs. OpenSearch vs. Tigris

System Properties Comparison Google Cloud Datastore vs. Microsoft Access vs. OpenSearch vs. Tigris

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

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

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store

Relational DBMS

Search engine

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Vector DBMS

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

cloud.google.com/datastore

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

github.com/opensearch-project
opensearch.org

www.tigrisdata.com

Technical documentation

cloud.google.com/datastore/docs

developer.microsoft.com/en-us/access

opensearch.org/docs/latest

www.tigrisdata.com/docs

Developer

Google

Microsoft

Amazon Web Services

Tigris Data, Inc.

Initial release

2008

1992

2021

2022

Current release

1902 (16.0.11328.20222), March 2019

2.5.0, January 2023

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

Apache Version 2.0

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

C++

Java

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

All OS with a Java VM

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

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

yes

Typing

predefined data types such as float or date

yes, details here

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language (GQL)

yes

but not compliant to any SQL standard

SQL-like query language

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

Java API
RESTful HTTP/JSON API

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

using Google App Engine

yes

since Access 2010 using the ACE-engine

yes

Triggers

Callbacks using the Google Apps Engine

yes

since Access 2010 using the ACE-engine

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

yes, using FoundationDB

In-memory capabilities

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

User concepts

Access control

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

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

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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

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...
» more

Licensing and pricing models

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

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