NDB Cluster 8.0 and also how these applications have developed over the
There is a presentation at slideshare.net accompanying this blog.
The first major NDB development project was to build a prototype of a
number portability application together with a swedish telecom provider.
The aim of this prototype was to show how one could build advanced
telecom applications and manage it through standardised interfaces.
The challenge here was that the telecom applications have stringent
requirement, both on uptime and on latency. If the database access
took too long time the telecom applications would suffer from
abandoned calls and other problems. Obviously the uptime of the
database part had to be at least as high as the uptime of the
telecom switches. Actually even higher since many telecom databases
are used by many telecom switches.
In the prototype setup NDB Cluster was running in 2 SPARC computers
that was interconnected using a low latency SCI interconnect from
Dolphin, the SPARC computer was also connected to the AXE switch
through Ethernet that connected to the central computer in the
AXE switch through a regional processor. This demo was developed
in 1997 and 1998 and concluded with a successful demo.
In 1999 a new development project started up within a startup arm
of Ericsson. In 1999 the financial market was very hot and to have
instant access to stock quotes was seen as a major business benefit
(it still is).
We worked together with a swedish financial company and together with
them we developed an application that had two interfaces towards
NDB Cluster. One was the feed from the stock exchange where stock
order was fed into the database. This required low latency writes into
NDB Cluster and also very high update rates.
The second interface provided real-time stock quotes to users and
other financial applications. This version was a single-node
We delivered a prototype of this service that worked like a charm in
2001. At this point however the stock markets plunged and the financial
markets was no longer the right place for a first application for NDB
Thus we refocused the development of NDB Cluster back towards the
telecom market. This meant that we focused heavily on completing the work
on handling node failures of all sorts. We developed test programs that
ran thousands of node failures of all sorts every day. We worked with a
number of prospective customers in 2002 and 2003 and developed a number
of new versions of NDB Cluster.
The first customer that adopted NDB Cluster in a production environment
was Bredbandsbolaget, we worked together with them in 2003 and 2004 and
assisted them in developing their applications. Bredbandsbolaget was and
is an internet service provider. Thus the applications they used NDB
Cluster in was things like a DNS service, a DHCP service and so forth.
We worked close with them, we even had offices in the same house and on
the same floor, so we interacted on a daily basis. This meant that the
application and NDB Cluster was developed together and had a perfect
fit for each other. This application is still operational and have been
so since 2004. I even had Bredbandsbolaget as my own internet service
provider for 10 years. So I was not only developing NDB Cluster, I was
also one of its first users.
In 2003 NDB Cluster development was acquired by MySQL and we changed the
name to MySQL Cluster. Nowadays there are other clustering products within
the MySQL area, so to distinguish NDB Cluster I sometimes use
MySQL NDB Cluster and sometimes simply NDB Cluster. However the product
name is still MySQL Cluster.
After Bredbandsbolaget we got a number of new large customers in the telecom
area. Many of those telecom customers have used LDAP as the application
protocol to access their data since there was some standardisation in the
telecom sector around LDAP. To assist this there is a storage engine
to access NDB Cluster from OpenLDAP. One example of such a telecom
application is Juniper SBR Carrier System that has a combination of
SQL access, LDAP access, HTTP access, RADIUS acces towards NDB Cluster.
NDB is used in this application as a Session State database.
All sorts of telecom applications remains a very important use case for
NDB Cluster. One interesting area of development in the telecom space is
5G and IoT that will expand the application space for telecom substantially
and will expand also into self-driving cars, smart cities and many more
interesting applications that require ultra high availability coupled with
high write scalability and predictable low latency access.
Coming back to financial applications this remains an important use case
for NDB Cluster. High write scalability, ultra high availability and
predictable and low latency access to data is again the keywords that
drives the choice of NDB Cluster in this application area.
The financial markets also add one more dimension to the NDB use cases.
Given that NDB can handle large amounts of payment, payment checks,
white lists, black lists and so forth, it is also possible to use
the data in NDB Cluster for real-time analysis of the data.
Thus NDB Cluster 8.0 have focused significantly on delivering more
capabilities in the area of complex queries as well. We have seen
many substantial improvements in this area.
More and more of our users work with standard SQL interfaces towards
NDB Cluster and we worked very hard on ensuring that this provides
low latency access patterns. All the traditional interfaces towards
MySQL will also work with NDB Cluster. Thus NDB can be accessed from
all programming languages that one can use to access MySQL from.
However many financial applications are written in Java. From Java
we have a NDB API called ClusterJ. This API uses a Data Object Model
that makes it very easy to use. In many ways it can be easier to
work with ClusterJ compared to working with SQL in object-oriented
The next application category that recognized that NDB Cluster had a
very good fit for them was the Computer Gaming industry. There is a
number of applications within Computer Gaming where NDB Cluster has
a good fit. User profile management is one area where it is important
to always be up and running such that users can join and leave the
games at any time. Game state is another area that requires very high
write scalability. Most of these applications use the SQL interface
and many applications use fairly complex SQL queries and thus benefit
greatly from our improvements of parallel queries in NDB Cluster 8.0.
An interesting application that was developed at the SICS research
institute in Stockholm is HopsFS. This implements a file system in the
Hadoop world based on Hadoop HDFS. It scales to millions of
file operations per second.
This means that NDB Cluster 8.0 is already used in many important
AI applications as the platform for a distributed file system.
In NDB Cluster 8.0 we have improved such that write scalability is
even higher also when the writes are large in volume. NDB Cluster 8.0
scales to updates measured in GBytes per second even in a 2-node
cluster and in a larger cluster one can reach almost hundreds of
GBytes per second.
Thus NDB Cluster 8.0 is a very efficient tool to implement modern
key-value stores, distributed file systems and other highly
NDB Cluster 8.0 is also a perfect tool to use in building many of the
modern applications that is the base of cloud applications. This is
one more active area of development for MySQL NDB Cluster.
Obviously all sorts of Web applications is also a good fit for NDB
Cluster. This is particularly true with developments in NDB Cluster
7.6 and 8.0 where we improved latency of simple queries and
implemented a shared memory transporter that makes it very
efficient to setup small clusters with low latency access to all data.
For web applications we also have a NodeJS API that can access
NDB Cluster directly without going through a MySQL Server.
In a keynote in 2015 GE showed some templates for how to setup
NDB Cluster in GE applications for the health-care industry. More on
architectures for NDB Cluster in a later blog.