Is SAP HANA the future of PLM databases

February 7, 2013

I’m on the road in Europe this week. Europe met me with snow in Zurich and not very reliable internet connection later in Germany. On the plane, I was reading about future investments of SAP in HANA (new in-memory database) that suppose to revolutionize enterprise software industry. Navigate to the following link and have a read – SAP’s HANA Deployment Leapfrogs Oracle, IBM And Microsoft. I found the following passage very interesting.

What SAP has done is to provide one database that can perform both business analysis and transactions, something its rivals are able to provide only by using two databases, according to Gartner analyst Donald Feinberg. “It’s the only in-memory DBMS (database management system) that can do data warehousing and transactions in the same database. That’s where it’s unique.”

Databases is a fascinating topic. At the end of the day, the enterprise software industry (and not only) is solely relies on database for most of the applications. The days PDM apps were running on proprietary databases and filesystems gone completely. The last one I knew was PDM workgroup. In my view, SolidWorks is still running bunch of customers using this solution, but nobody is taking database-less solution seriously these days. Most of PDM and PLM applications are running on MS SQL and Oracle databases. Despite PLM power of IBM, I haven’t seen any significant usage if DB2 for PDM/PLM. Another interesting quote, I found about HANA is related to competition. According to author it will take few more years until Microsoft and Oracle will be able to catchup.

SAP has taken a big step ahead of rivals IBM, Microsoft and Oracle with the announcement on Thursday that its in-memory database called HANA is now ready to power the German software maker’s business applications. The pronouncement is sure to darken the mood of competitors, who one analyst says will need several years to match what SAP has accomplished.

I’ve been writing about HANA and applications before on my blog. Take a look here. Also, you can find lots of interesting resources online here. Applications of HANA database are interesting and when it comes to analyzes of massive amount of data makes a lot of sense in context of product development and manufacturing.

For SAP customers, HANA-powered applications can speed up the sales process dramatically. For example, today when salespeople for a large manufacturer takes a large order from a customer, they may not be to say on the spot exactly when the order will be fulfilled. That information often comes hours later after the numbers are run separately through forecasting applications.

What is my conclusion? Customers are interested in real solutions that can save money to them. Technology is less relevant in that case. Ability to answer practical questions is more important. SAP has money and customers. Many years, SAP is using database solution from main competitors – Oracle and Microsoft. Will SAP be able to pull new technology to revolutionize this market? Will Microsoft, Oracle and open source databases will be able to catch up this game? An interesting question to ask these days… Just my thoughts.

Best Oleg

What PLM vendors need to know about noSQL databases?

December 14, 2012

Relational databases is a very mature set of technologies. We use RDBM (Relational databases) practically everywhere these days. It is hard to imagine enterprise software and PDM/PLM systems these days without relational databases. At the same time, the new class of database management solution is coming. It called NoSQL (Not Only SQL). I posted about noSQL few times. You can refresh your memory by navigating to the following link. First time this term came in use back in 1998 as "noREL" databases. Later in 2009, the term noSQL was proposed for "to label the emergence of a growing number of non-relational, distributed data stores that often did not attempt to provide atomicity, consistency, isolation and durability guarantees that are key attributes of classic relational database systems". NoSQL database solutions are widely used today in web and mobile applications. I can see a growing number of noSQL database usage in business intelligence and master data management applications.

NoSQL is not a single database. This is a name for a broad set of data management or database technologies focusing outside of RDBMS world. The technologies and terminologies behind this term is new. PDM/PLM vendors ignored noSQL database management solutions until very recently. It made me think to provide a quick summary of what stands behind this broad term and what PDM/PLM uses cases it can support.

Key-value (KV) databases

KV stores is a simplest database model in noSQL world. It stores "keys" and associated "value". Basically your database is a storage of pairs of key-value. Some databases support more complex structure behind values such as complex values (list, hash), but it is not required. One of interesting PDM/PLM use cases is to store list of files as a key-value database. In such a case, file name is a key (including full path) and value is actually the content of the file. Examples of KV stores are Riak and Redis.

Colum-oriented databases

This type of database is very close to RDBMS. The main difference is that columnar data model designed to keep data from every column in the table together. It is an opposite solution to RDBMS, which keeps the data for a specific row together. It allows to add a column to a table in a very "inexpensive" way. Each row may have a different set of columns. This type of databases are good for reporting and business intelligence solutions. Columnar data model impacted few PDM/PLM core modeler development available today at the market, by providing a higher level of flexibility in data modeling. Example of column-oriented databases is HBase.

Document-oriented database

Document databases are managing data in a form of documents. Documents can be different and have different structure. The last thing makes document oriented databases very flexible. Some implementations of document oriented databases such as MongoDB provides you an ability to run query against the document structures as well as do mapreduce computations as well. Depends on the need you can consider different DO-databases. Examples of these databases are – MongoDB and CouchDB. You can consider document database in PDM/PLM in two cases – the need for high-performance scalable document store and free form data modeling.

Graph-databases and triple stores

Graph data model is dealing with highly interconnected data. It contains nodes and relationships between nodes. Both nodes and relationships can have properties (key-value pairs). This data model becomes really important when you are traversing through the nodes with a specific relationships. There are many situations in PDM/PLM applications when we need to traverse data efficiently. Graph database (and predecessors – object databases) has a great potential to bring a value here. The example of graph databases is Neo4j. Also, a specific case of graph databases is so-called triplestores managing information using triples (subject-predicate-object). Examples of triple stores are OWLIM and AllegroGraph. Also triple stores are supported by Oracle and IBM DB2

CAP Theorem and why PLM systems need to use more than one database?

In computer science CAP theorem states that it is impossible for a distributed computer system to simultaneously provide all there guarantee Consistency (all nodes see the same data at the same time), Availability (a guarantee that every request receives a response about whether it was successful or failed) and Partition tolerance (the system continues to operate despite arbitrary message loss or failure of part of the system). Navigate here to read more. It is a question of priorities and a tradeoff between what requirements you need to satisfy in your system. PLM systems are facing significant challenges in a variety of data types, retrieve patterns and data scaling. Usage of different strategies in database management can improve existing solutions.

What is my conclusion? PLM is a multidisciplinary approach. It handles variety of data and connected to many places in the organization. Design, engineering, manufacturing, supply chain, support, services. The specialty of PLM environment is to get connected to all data suppliers and interplay with different sources of data. From that standpoint, data behaves like oil – located in multiple places, but needs to be extracted. You need to use different tools to get it out. Think about different database as a tool-set to process and get access to data in a most efficient way. Just my thoughts…

Best, Oleg

What is the right data model for PLM?

August 17, 2012

I think the agreement about importance of the data model among all implementers of PDM / PLM is almost absolute. Data drives everything PDM / PLM system is doing. Therefore, to define the data model is the first step in many implementations. It sounds as something simple. However, there is implied complexity. In most cases, you will be limited by the data model capabilities of PLM system you have. This is a time, I want to take you back in history.

Spreadsheet Data Model

Historically, it became the most commonly used data model. And the reason is not only because Excel is available to everybody. In my view, it happened also, because tables (aka spreadsheets) is a simple way to think about your data. You can think about table of drawings, parts, ECOs. Since almost everything in engineering starts from Bill of Material, to think about BOM table is also very simple. The key reason why in many cases spreadsheet model became so wide-accepted are simplicity and absolute flexibility. Engineers love flexibility, and this data model became widely popular.

Relational Data Model

This data model was developed by Edgar Codd back more than 50 years ago. Database software runs on top of this model, and we got what known today as RDBMS. Until second half of the last decade, it was the solution all PDM /PLM developers were relying. First PDM systems were developed based on RDBMS. However, they had low flexibility. Because of rigorous rules of this model, making changes was considered as not a simple task. One of the innovations of late 1990s was to develop a flexible data model as an abstraction on top of RDBS. Almost all PDM/PLM systems in production today are using object abstractions developed on top of the relational data model.

The challenges of Spreadsheets and Relational Databases

Despite these technologies are proven and used by many mainstream applications, it is far from perfection. One of the product development demands is flexibility. Spreadsheet model can deliver that, but gets very costly within the time. Relational data model can combine flexibility and support manageability of data. However, it becomes to make a change in these models is costly. Identification, openness and expandability is problematic in relational data models opposite to some other web-based solutions.

Future data models – NoSQL, RDF, etc.

Thinking about what comes in the future, I want to spell to buzzwords – NoSQL and Semantic Web. I can see a growing amount of solutions trying to adopt a variety of new data platforms. NoSQL comes to the place as an alternative solution to Relational Database. If this is a first time you’re hearing this buzzword, navigate to the following Wikipedia link. NoSQL is not all the same. It combined the whole group of solutions such a key-value stores, object databases, graph databases, triple store. Semantic web is collaborative movement led by W3C. The collection of Semantic Web technologies (RDF, OWL, SKOS, SPARQL, etc.) provides an environment where application can query that data, draw inferences using vocabularies, etc. Part of these standards something called Linked Data – a collection of data set in open formats (RDF) that shared on the web.

What is my conclusion? Many of the technologies used by PLM companies these days are outdated and came from the past 20-25 years. There is nothing wrong in these technologies. They are proven and successfully used for many applications. However, in order to achieve the next level of efficiency and embrace future of PLM, new horizons need to be explored. Data flexibility, openness and interoperability – these elements are absolutely important in the future of PLM. Options to use future data models coming from past 10 years of web experience need to be explored. Important. Just my thoughts…

Best, Oleg


PLM, RDBMS and Future Data Management Challenges

January 5, 2012

It is not unusual to hear about problems with PLM systems. It is costly, complicated, hard to implement and non-intuitive. However, I want to raise a voice and speak about data management (yes, data management). Most of PDM/PLM software is running on top of data-management technologies developed and invented 30-40 years ago. The RDBM history is going back to the invention made by Edgar Codd at IBM back in 1970.

I was reading Design News article – Top automotive trends to watch in 2012. Have a read and make your opinion. One of trends was about growing complexity of electrical control units. Here is the quote:

As consumers demand more features and engineers comply, automakers face a dilemma: The number of electronic control units is reaching the point of unmanageability. Vehicles now employ 35 to 80 microcontrollers and 45 to 70 pounds of onboard wiring. And there’s more on the horizon as cameras, vision sensors, radar systems, lanekeeping, and collision avoidance systems creep into the vehicle.

It made me think about potential alternatives. Even if I cannot see any technology these days that can compete on the level of cost, maturity and availability with RDBMS, in my view, now it is a right time to think about future challenges and possible options.

Key-Value Store

These types of stores became popular over the past few years. Navigate to the following article by Read Write Enterprise –Is the Relational Database Doomed? Have a read. The article (even if it a bit dated) provides a good review of key-value stores as a technological alternative to RDBMS. It obviously includes pros and cons. One of the biggest "pro" to use key-value store is scalability. Obvious bad is an absence of a good integrity control.

NoSQL (Graph databases)

Another interesting example of RDBMS alternative is so-called noSQL databases. The definition and classification of noSQL databases is not stable. Before jumping into noSQL bandwagon, analyze the potential impact of immaturity, complexity and absence of standards. However, over the last 1-2 year, I can see a growing interest into this type of technology. Neo4j is a good example you can experiment with in case you are interested.

Semantic Web

Semantic web (or web of data) is not a database technology. Opposite to RDBMS, Key-value stores and graph databases, semantic web is more about how to provide a logical and scalable way to represent data (I wanted to say in "semantic way", but understand the potential of tautology :)). Semantic web relies on a set of W3C standard and combines set of specification describing ways to represent and model data such as RDF and OWL. You can read more by navigating to the following link.

What is my conclusion? I think, the weak point of existing RDBMS technologies in the context of PLM is a growing complexity of data – both from structural and unstructured aspects. The amount of data will raise lots of questions in front of enterprise IT in manufacturing companies and PLM vendors. Just my thoughts…

Best, Oleg

Will PLM Get Troubled by Future FOSS databases?

December 17, 2009

The following article in TechWords “The New FOSS Frontier: The Database Market” drove me to think about PLM and RDBS relationships from a different angle. For PLM, as for all enterprise applications these days, RDBMS is almost commodity. PLM supports all of them (actually there are not so many – Oracle, MS SQL Server and DB2, who else?), cost of RDBS solution is insignificant since it either included into premium cost of PLM or RDBMS is already available in the organization.

Nevertheless, I think, things may go wrong. I see two aspects where PLM providers can be impacted. Here is my view on this.

1. Cost of PLM software. Introduction of FOSS into the enterprise domain can drive customers to think about the future cost cutting in software. With today’s huge payments for RDBMS, enterprises don’t see any other alternatives and continue to pay to ERP, PLM and other vendors. Tomorrow their expectation will be different.

2. Reliance on RDBMS vendor status quo. PLM systems are heavily relying on databases in general. Also, some of PLM systems are tuned for a specific RDBMS features. What will happen if PLM will lose RDBM anchor in enterprise?

So, what is my thoughts and conclusion today? Ringing bell of free should awake some of the sleeping PLM behemoths. Tomorrow the situation be a different and customer’s perception on enterprise software can change, just if a small fraction of enterprises, will be switching from licensed RDBMS systems to FOSS rivals. So, PLM better to come prepared.

Just my thoughts.
Best, Oleg


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