DBMS > Datomic vs. Google Cloud Spanner vs. Microsoft Access vs. RocksDB vs. SAP Advantage Database Server

System Properties Comparison Datomic vs. Google Cloud Spanner vs. Microsoft Access vs. RocksDB vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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.)

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.datomic.com

cloud.google.com/spanner

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

rocksdb.org

www.sap.com/products/advantage-database-server.html

Technical documentation

docs.datomic.com

cloud.google.com/spanner/docs

developer.microsoft.com/en-us/access

github.com/facebook/rocksdb/wiki

Developer

Cognitect

Google

Microsoft

Facebook, Inc.

Sybase, SAP

Initial release

2012

2017

1992

2013

1993

Current release

1.0.7075, December 2023

1902 (16.0.11328.20222), March 2019

9.2.1, May 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Bundled with Microsoft Office

Open Source

BSD

commercial

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, Clojure

C++

Server operating systems

All OS with a Java VM

hosted

Windows

Not a real database server, but making use of DLLs

Linux

Linux
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

but not compliant to any SQL standard

yes

APIs and other access methods

RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

C++ API
Java API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Clojure
Java

Go
Java
JavaScript (Node.js)
Python

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

C
C++
Go
Java
Perl
Python
Ruby

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

since Access 2010 using the ACE-engine

yes

Triggers

By using transaction functions

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication with 3 replicas for regional instances.

none

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

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

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

but no files for transaction logging

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

caching of (temporary) tables can be configured

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

fine grained access rights according to SQL-standard

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