DBMS > Drizzle vs. Google Cloud Bigtable vs. Graph Engine vs. SAP Advantage Database Server

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. Graph Engine vs. SAP Advantage Database Server

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Primary database model

Relational DBMS

Key-value store
Wide column store

Graph DBMS
Key-value store

Relational DBMS

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Website

cloud.google.com/bigtable

www.graphengine.io

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

Technical documentation

cloud.google.com/bigtable/docs

www.graphengine.io/docs/manual

Developer

Drizzle project, originally started by Brian Aker

Google

Microsoft

Sybase, SAP

Initial release

2008

2015

2010

1993

Current release

7.2.4, September 2012

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

MIT License

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

C++

.NET and C

Server operating systems

FreeBSD
Linux
OS X

hosted

.NET

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

with proprietary extensions

yes

APIs and other access methods

JDBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

RESTful HTTP API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C++
Java
PHP

C#
C++
Go
Java
JavaScript (Node.js)
Python

C#
C++
F#
Visual Basic

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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