There are so many products which are rdbms like oracle,mysql,SqlServer etc....
But what about dbms related products?Is foxpro dbms ?
All these.
A growing segment of the non-rdbms market are the document-oriented databases (disclaimer: some of these are implemented on top of an RDBMS underneath, so all aren't "non-RdBMS").
There are many databases that aren't RDBMS though, this is just one of the most active alternatives at the moment, so worth noting IMO.
Information Management System (IMS) from IBM: [Record based data model – Hierarchical data model]
Integrated Data Management System(IDMS) from Honeywell [Record based data model – Network data model]
MS-Access is a classical example for DBMS which is not a RDBMS.
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I'm getting familiar with the greenplum solution concepts, and trying to understand whether, and if so, when the organisation I work for should use this solution. Our conceptual idea is to setup a kind of central 'datastore' suitable for both OLTP and OLAP access.
My research: this article suggests Greenplum is more suitable for OLAP, and PostgreSQL for OLTP. But I also read about Greenplum improvements for OLTP processing. And in favour of Postgresql, there are also articles like this that suggest that OLAP (eg, a datawarehouse implementation) can be done by means of Postgresql.
So my question is: how to move forward, and what are the main criteria to decide? For example, in case we now have a just a few TB's (1-5), start with a Postgresql cluster (for OLTP+OLAP), and when data volumes grow, move on to Greenplum? Or start straight away with Greenplum?
maybe use postgres if it can handle your use case. If you have you have too much data and need to finish reports and analytics faster; change to greenplum
i have a problem where in i need to store the users's address data which can come from different vendors in different format. once i have the data i need to do some cleaning and wrinkling and run the de-duplication process to get the clean structured data. once the data is clean, i may have to pick the different attributes of address from different vendors based on some complex logic which is not defined yet. my question is
1) which database i should use i.e. NOSQL database family like document/keyvalue/dynamoDB etc or RDBMS with MPP database like redshift or azure data warehouse
2) NOSQL DB like mongoDB provide the flexibility of schema but at the same time the queries or de-duplication process is not something inbuilt for these databases.
if anyone can guide me on this i shell be very thankful for him
Thanks
Atul
I am still learning about NoSQL databases and their capabilities. One of my concerns is being able to apply something similar to Oracle Security Labels or some type of row level security. Do any NoSQL databases support something similar to this? Is this even possible with document based db's or column family style databases?
I was reviewing some documents for making my database perform better and I came across with "OLAP" pre-aggregation term. I was wondering if OLAP is a tool or or methodology or approach. For example my DBMS is postgresql and I am working on a big databse. To speed up I have to use some aggregation and pre-aggregation methods. How OLAP can be helpful?
OLAP is a database role. When storing OLAP data in the db, typically you aren't running live transactional information off the db, but rather keeping it around for analytical and business intelligence reasons.
It isn't a tool. It isn't an approach either, since some approaches are needed for OLAP but some are helpful together in transactional environments as well.
In general you shouldn't think about speeding up an application by incorporating OLAP into it. Instead you would look at separating out reporting functions into a separate db server, and import the data periodically, and then separate data feeds from operation data stores, etc. This is a very different field than transactional application development.
when we say rdbms that means it may be oracle, my sql, ms access etc.. But for dbms what are the examples. Is there any example or it just the concept?.
A DBMS is a database management system. There are two crucial features a DBMS must provide:
storing data
standardised access to the data
The second function is the crucial one. I can connect to a DBMS with a generic client (e.g. through JDBC and discover the organisation of the data stored therein. I can do this because a real DBMS maintains metadata - data about the date it stores - in a data dictionary or an INFORMATION_SCHEMA.
So we can see that flat files do not constitute a DBMS. They handle the first part, persistence, easily enough, but they fail on the second: only the application (or person) which wrote the data can interpret the data structure. This means that spreadsheets don't count as a DBMS either (although a case can be made for XML files).
An RDBMS is a particular type of DBMS which implements Codd's famous Twelve Rules. Many database theoreticians would arge that the products you list (Oracle, MySQL, MS Access) are examples of SQL DBMS rather than RDBMS because they fail to satisfy two or more of Codd's rules: they all fail Rule 0 and then at least one other rule.
There are other types of DBMS. There is the hierarchical form, of which the most venerable is MUMPS . There are object-oriented OODBMS, such as Intersystems Cache. There are network (graph) DBMS e.g. IDMS and Neo4J. And thene there's the whole raft of other NoSQL databases most of which probably qualify as DBMSes.
dbms = database management system
rdbms = relational database management system
So every rdbms is also a dbms.
You might want to name Gemstone, an OODBMS, or Cache, a hierarchical one.
Database management system has a list of links to various types of DBMSs which then link to lists of examples for that type, for example a list of Object DBMSs