DBMS > Ehcache vs. Elasticsearch vs. Google BigQuery vs. IBM Db2 warehouse vs. Microsoft Access

System Properties Comparison Ehcache vs. Elasticsearch vs. Google BigQuery vs. IBM Db2 warehouse vs. Microsoft Access

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Large scale data warehouse service with append-only tables

Cloud-based data warehousing service

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.)

Primary database model

Key-value store

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Website

www.ehcache.org

www.elastic.co/elasticsearch

cloud.google.com/bigquery

www.ibm.com/products/db2/warehouse

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

Technical documentation

www.ehcache.org/documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

Developer

Terracotta Inc, owned by Software AG

Elastic

Google

IBM

Microsoft

Initial release

2009

2010

2014

1992

Current release

3.10.0, March 2022

8.6, January 2023

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Elastic License

commercial

Bundled with Microsoft Office

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++

Server operating systems

All OS with a Java VM

hosted

Windows

Not a real database server, but making use of DLLs

Data scheme

schema-free

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

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.

Import/export of XML data possible

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

but not compliant to any SQL standard

APIs and other access methods

JCache

Java API
RESTful HTTP/JSON API

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

Java

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

PL/SQL, SQL PL

yes

since Access 2010 using the ACE-engine

Triggers

yes

Cache Event Listeners

yes

by using the 'percolation' feature

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

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

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

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

In-memory capabilities

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

yes

Memcached and Redis integration

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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

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