What NoSQL database to choose

Big Data application requirements are usually very extensive and might not fit into one database technology. The list of these requirements can be huge and specific. Some general ones are below:

•  Handling huge amounts of unstructured data
•  Combination from search and analytical type of queries
•  Denormalized data patterns
•  Support for high volume writes and read volumes that are not always predictable
•  High availability
•  No downtime deployments
•  …

Perhaps that is the reason why NoSQL solutions are very much application and situation specific based on every product in corresponding category functionality and features. Usually no one NoSQL database matches all the application requirements like usual General-Purpose RDBMS systems. It depends a lot on the application architecture and what NoSQL database fits better you have to decide.

The NoSQL databases have specific characteristics to showcase and they perform best if used for that purpose. So you cannot use a Key-Value store when you need a Graph or Document database for example, while Relational database systems (RDBMS) are all quite compatible.

Then what NoSQL database to choose? Read more

NoSQL database types comparison in examples

NoSQL database type comparison in examples

NoSQL database type comparison in examples

NoSQL (Not only SQL) term covers different database technologies that were developed to handle huge unstructured data volumes and the frequency in which this data is accessed as well as performance and processing needs. NoSQL is NOT a database that we used to think. In my understanding NoSQL is a range of technologies, approaches and even projects directed to realization of unstructured – so-called Big Data models – that have considerable differences to traditional Relational Database Management Systems (RDBMS). The main goal of NoSQL storage systems is to resolve unstructured data manipulation issues that are not efficiently managed by RDBMS. Note, I’m not saying RDBMS can not manage the same unstructured stuff. On the contrary, with new features the modern RDBMS can do more and more in the Big Data area but obviously not as efficient as some NoSQL solutions.

In practice, “NoSQL” means non-relational database, but this concept of NoSQL does not disclaim SQL language completely often however querying these databases in data-model specific way. Anyway, the underlying query execution strategy is usually very different from the way a traditional RDBMS would use.

Many of the NoSQL platforms allow for RESTful interfaces to the data, while others offer query APIs. NoSQL storage systems are often used in combination with Hadoop Distributed File System that enables large scale computations on clustered servers.

Important to mention that NoSQL databases are not General-Purpose Database Management Systems, but they are very specific to application use cases. Also, NoSQL engines are not compatible to each other and NOT to the General-Purpose DBMSs.

See below some common attributes of noSQL databases:

• Specialized databases for various scenarios
• They manage Unstructured Data (Big Data)
• Often as pure data stores offering just standard APIs for developers
• Non-Relational data model is optimized for the type of data being stored
• Underlying query execution done in data-model specific way
• Usually do NOT support ANSI SQL and ACID standards
• Usually do NOT support transactions and data consistency across entire DB
• Usually optimized for high performance data loads and reads
• Data Updates are often slow
• Table Joins are usually NOT supported
• Usually do NOT include comprehensive Database Manageability features

The data in NoSQL DB engines are represented in a view of hash-tables, tries, documents etc. Based on this representation approach they are divided into four major categories or types: Key-Value Stores, Document Databases, Column Stores and Graph databases. See their description below:
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Oracle Openworld 2019 Major Technology Announcements

oracle openworld 2019 technology announcements highlights

Below are major technology announcements or highlights that came from the Oracle OpenWorld conference 2019. Most of them are round Oracle Cloud (OCI), Oracle Autonomous database, Exadata and Linux

Redwood – New User Experience Design 

If you navigate to www.oracle.com or cloud.oracle.com you see the new Oracle look & feel called „Redwood“. In future all Oracle Presence will follow this new Modern UX Design, including GUI of Cloud & On-Premises.

Connectivity between OCI & Azur Cloud

Oracle announces close partnership with Microsoft in the area of Oracle Cloud Infrastructure & Microsoft Azure by introducing High Speed Interconnect between OCI & Azur Clouds:

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Oracle database 12cR2 new patching concept RU RUR

Oracle database 12cR2 new patching RU RUR

The new database patching for Oracle 12cR2 (12.2) and above using new RUs and RURs patches replaces the old patching concept. Means, the legacy terms and patches Patchset, Patchset Update (PSU), Database Bundle Patch, Critical Patch Update (CPU) will no longer be meaningful for 12.2 database software. The new patches will be applied in the same way using opatch utility with ability using RAC Rolling or Data Guard/GG switchover techniques.

The major points about the new patching concept are below:

New quarterly Release Update (RUs)
– More aggressive patching for test / dev and early production roll-outs -> more testing required
– Released quarterly (Jan, Apr, Jul, Oct)
– Proactive, highly tested bundles of critical fixes
– Include all security fixes for the same quarterly cycle
– Enable customers to avoid known issues.
– Might contain small, important new features
– Query optimizer fixes that can change execution plans might be included but must be enabled manually by the customer after patching.
– Separate Database RU, Grid Infrastructure RU, and OJVM RU available

New quarterly Release Update Revisions (RURs)
– A bit similar to former PSUs
– Less aggressive pathing for stable production environments -> less testing required
– Released quarterly (Jan, Apr, Jul, Oct) Read more

Oracle Open World Conference 2017 Highlights

JavaOne and Oracle Open World Conference 2017JavaOne & Oracle OpenWorld (OOW) conference is one of the biggest and most important technology conference in the world. It hosts tens of thousands of attendees as well as millions online who want to connect, learn and explore industry trends and breakthroughs driven by IT technology. The conference offers more than 2,500 educational sessions, hundreds of demos and hands-on labs, plus exhibitions from more than 400 partners and customers from around the world.

The conference does not focus purely on databases. There are many more interesting technology areas presented from HW, OS and software development to modern IT trends like Cloud, Big Data, Blockchain, Internet of Things, Machine Learning, etc. But what about the database? Is Oracle not a pure database provider? No, it was probably long time back, but NOT ANY MORE.

Below are a few major topics that were dominating at the last OOW


Oracle is aggressively scaling its cloud business and effectively catching-up with competitors like Amazon (AWS), Azur and Salesforce introducing at OOW17 an array of new Cloud offerings and enhancements and demonstrating its cost efficiency and unbeatable Infrastructure performance. At the same time comparing these all the way against AWS. For example, Larry Ellison (Oracle Founder & CTO) stated that Oracle Cloud would cost at least 50% less of your AWS bill and they would write this in the contract.
The recent launch of Oracle data Centers in Frankfurt supporting European Availability region can only confirm serious Oracle intention in the Cloud business. I personally think that soon only a few large Cloud providers will cover the major Cloud market that in turn will be driven mostly by Software Cloud Services (SaaS and partly PaaS). And there is a big chance that Oracle will be soon in the Cloud leaders caused by a large range of own quality software, modern Java development platform as well as own cost efficient HW, OS and Virtualization stack.

Machine learning

What is this thing by the way? Read more

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