DBMS > Ehcache vs. Google BigQuery vs. Microsoft Access vs. NSDb vs. Trafodion

System Properties Comparison Ehcache vs. Google BigQuery vs. Microsoft Access vs. NSDb vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

A widely adopted Java cache with tiered storage options

Large scale data warehouse service with append-only tables

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.)

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Transactional SQL-on-Hadoop DBMS

Primary database model

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

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

www.ehcache.org

cloud.google.com/bigquery

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

nsdb.io

trafodion.apache.org

Technical documentation

www.ehcache.org/documentation

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

nsdb.io/Architecture

trafodion.apache.org/documentation.html

Developer

Terracotta Inc, owned by Software AG

Google

Microsoft

Apache Software Foundation, originally developed by HP

Initial release

2009

2010

1992

2017

2014

Current release

3.10.0, March 2022

1902 (16.0.11328.20222), March 2019

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Bundled with Microsoft Office

Open Source

Apache Version 2.0

Open Source

Apache 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.

Implementation language

Java

C++

Java, Scala

C++, Java

Server operating systems

All OS with a Java VM

hosted

Windows

Not a real database server, but making use of DLLs

Linux
macOS

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, 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.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language

yes

APIs and other access methods

JCache

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Java
Scala

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

Java Stored Procedures

Triggers

yes

Cache Event Listeners

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

but no files for transaction logging

Using Apache Lucene

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)

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

fine grained access rights according to SQL-standard

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