There are some game changer technologies in data management as we can see lately. For long, database technologies had been revolving around the concept of relational database management and SQL-based programming. However, the needs of today’s enterprises in terms of unstructured data management and big data administration are changing rapidly. Here, we will discuss the major trends which mostly affect this change.
1. The concept of engineered databases
This is a pretty simple idea; instead of the enterprises building their databases from scratch, Oracle, the leading player in enterprise database management, brings together efficient DB hardware and try to optimize their software applications to run a database at peak. Say, for example, the system itself can move the query processing to storage in order to provide analytical evaluations faster.
This new approach by Oracle is making a move in the database management industry. With more than a decade of industrial presence and thousands of corporate customers, Oracle is all set to lead this movement in a big way. Moreover, this approach of engineered databases sounds to be pretty straightforward.
2. In-memory databases
There is no question about this trend. All database vendors now offer standard in-memory databases in their lineup. By using such data structures and advanced algorithms which specialize in in-memory data, the databases can run analytics even hundred times faster than the disk-based databases. Such kind of enormous speed may change the questions people may ask about data as the analysts may iterate the “what-if” queries by knowing they’ll get their answers in a few seconds. This is a revolutionary change compared to many hours of processing time in the past when it comes to analytics.
In this line, Oracle offers architecture with dual format architecture, in which a single database uses the best approach based on the use of the data, OLTP analysis or rows, and also in-memory column-based analysis for proper analytics. In-memory forms part in the Oracle Database 12c architecture, with which the companies will get it without changing any existing applications running on the Oracle Database. They get all the needed features as high scalability and anytime availability.
3. Software in Silicon
Rather than a product feature, experts at RemoteDBA.comconsider it as advancement in computer technology. We can expect in every possibility that the future database technologies will be largely different from what we see today. Oracle termed it as “software in silicon,” which is the concept of directly embedding the algorithms on to the microprocessors. The whole idea is that the processors may not be able to keep on adding more threads and cores, so performance and speed will be resulting from the use of algorithms in order to accelerate the core tasks like directly compressing onto the chip and encryption, etc.
We can cite three major aspects as a part of this advancement.
- At first, the SQL in the silicon will accelerate the in-memory speed and performance of the database.
- Capacity in silicon will help to get more and more data into the memory by using on-processor techniques like decompression at real-time.
- Thirdly, the encryption support in silicon will help to enhance the security features as workloads may also move to in-memory. Without such protection, the in-memory databases may prove out to be less secure than data on the disk.
This will be a great advancement in the industry in terms of how the database-centric processes work and how the silicon chips are made. You may see more such products appearing once Oracle establishes it and then other vendors also start following the technology.
4. Linkage of existing data into big data
The big data appliances now are capable of offering big data functions at a lower cost. Companies tend to generate big data while pursuing technology strategies like the Internet of Things or Artificial Intelligence with the use of live-stream data on customer trends. However, these deeper insights can only come from properly blending new form of big data with the data enterprises already have with them.
The DBAs will start to face the most important question much frequently as “how to integrate the existing operational data with big data?” Oracle put forth two solutions here as:
- Oracle Big Data Appliance which is a system that runs on Hadoop and Spark, which lets the IT teams build much faster at a much lower cost than building by their own.
- Oracle Big Data SQL which lets the business analysts run analytics parallel by running Oracle SQL queries on relational databases and also on Hadoop and the NoSQL databases. Compared to other queries run on big data sets, Oracle SQL stands as a much more sophisticated approach in which the approach is to make analytics simpler and more efficient to bring together big data.
5. Sharding made easier at a global scale
As we had seen above, the web-based companies with millions of users largely depend on database sharding than having one huge database to manage all users. Sharding will break it down to many manageable elements, but you can query on all the shards. This technology was developed a while ago which is much easier to deploy on NoSQL also. This is one major reason why many of the new-generation organizations like NoSQL databases.
Oracle is now offering the concept of native sharding in Oracle Database as the users have to take manual steps for sharding in the database. IT can be better enabled to manage shards with native sharding alongside getting all the default benefits of the Oracle database like top security and high availability etc. All these trends may give a new direction to database administrators in terms of future enterprise database management systems. Oracle is a tyrant to positively contribute to this change by creating many new systems and practices in terms of effective database management in the times of big data. Moreover, with the availability of data as a service, all types of users with access to any form of data will be able to store and analyze it through a standardized service layer. They can make use of data for competitive business advantages, and it will be a fundamental technology change in enterprise administration as to organizing and accessing data for business growth.