DBMS > Geode vs. Microsoft Access vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. Solr

System Properties Comparison Geode vs. Microsoft Access vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. Solr

Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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 Wide Column Store for rapid development using massive semi-structured datasets

Microsofts flagship relational DBMS

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

geode.apache.org

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

azure.microsoft.com/en-us/services/storage/tables

www.microsoft.com/en-us/sql-server

solr.apache.org

Technical documentation

geode.apache.org/docs

developer.microsoft.com/en-us/access

learn.microsoft.com/en-US/sql/sql-server

solr.apache.org/resources.html

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Microsoft

Apache Software Foundation

Initial release

2002

1992

2012

1989

2006

Current release

1.1, February 2017

1902 (16.0.11328.20222), March 2019

SQL Server 2022, November 2022

9.6.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Bundled with Microsoft Office

commercial

restricted free version is available

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Java

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Windows

Not a real database server, but making use of DLLs

hosted

Linux
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language (OQL)

yes

but not compliant to any SQL standard

yes

Solr Parallel SQL Interface

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Java API
RESTful HTTP/JSON API

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

yes

since Access 2010 using the ACE-engine

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java plugins

Triggers

yes

Cache Event Listeners

yes

since Access 2010 using the ACE-engine

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

ACID

but no files for transaction logging

optimistic locking

ACID

optimistic locking

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 rights per client and object definable

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

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

yes

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