Monthly Archives: December 2017

Best Useful Cloud Databases That You Need To Know

  • EnterpriseDB

PostgreSQL databases are the open source software and are targetted by EnterpriseDB but its actual to claim the fame of the capacity to work with Oracle database applications. There is a possibility by the organizations for using the applications written in on-premise Oracle databases via EnterpriseDB and it runs in cloud with Amazon Web Services and HP. There are scheduled backups and binary replication too.

  • Garantia Data

For running open source Redis and Memcached in-memory and Garantia offers a gateway service for its users. With the help of Garantia’s software, the automatic configuration of the open source data platforms assists the developer’s scale nodes for creating clusters and architect.

  • Google Cloud SQL

Two major products are the basis for Google’s cloud database service: Google Cloud SQL which is explained by Google as a MySQL-like fully relational database infrastructure, and Google BigQuery, an analysis tool to run the queries on big data sets stored in the cloud.

  • Microsoft Azure

SQL server technology is used by the Microsoft for offering a relational database for permitting the customers to access an SQL database on its cloud or SQL server instances for virtual machines. Hybrid databases are emphasized by the Microsoft for combining the data both on a customer’s premise and Azure cloud via SQL Data Sync.

  • MongoLab

There are various database platforms for choosing the NoSQL World like MongoDB. For accessing MongoDB its users are given permission on lots of major cloud providers along with AWS, Joyent, and Azure. MongoDB also combines with lots of platform as a Service (PaaS) tools at the application tier. Dedicated or shared environments are used for MongoLab to run and the shared one is quite costly.

  • Rackspace

In a cloud or a managed hosted database, Rackspace offers cloud databases for its product. The container-based virtualization is the emphasizes for Rackspace because of its cloud databases as it permits the higher performance of the database service when thought about the run on virtualized infrastructure. A SAN storage network is incorporated into the cloud databases and it depends on an OpenStack platform. Currently, a NoSQL database is declared by the Rackspace in the cloud from provider Cloudant.

  • SAP

The SAP is an enterprise software giant for playing the cloud with HANA which is a platform constructed on an in-memory technology. The company is complemented by the cloud database from HANA complements other on-premise database tools along with Sybase and is present in Amazon Web Services cloud. There are other non-database apps too for HANA along with the business management tools and application development.

  • StormDB

In the cloud, there is various database that runs in the fully distributed relational database for machine virtualization. For better performance, the StormDB officials claim the leads and are simply managed due as they don’t have to choose the size of the virtual machine and their database to run on. Although it is run on bare metal, the customers share the clusters of servers via StormDB and it promises the isolation among customer databases.

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NuoDB A Cloud Database

  • NuoDB

A client or a cloud relational database technology also called as NuoDB is SQL compliant and it has been called NewSQL. In the cloud, it has a distributed object architecture that it can work with. The term emergent architecture is the term used by NuoDB for their database and it implies that a new server is included for scaling up the database and it runs faster. Amongst lots of processors, the NuoDB database distributes the tasks for avoiding bottlenecks of data. A peer to peer messaging is used and it is ACID compliant.

A tiered approach is used by the database and it comprises of various redundant tiers of transaction engines (TE) and storage managers (SM). The data predictably can be approached by its assistance in the cloud. There are lots of NuoDB domains with various redundant Tes and Sms for running on the similar platform. There are various types of NuoDB working on various platforms like Mac OS, Windows, Solaris, x86, and JoyentCloud.

  • Uses of NuoDB

  1. Mobile Applications

There are lots of times various mobile apps are downloaded. For scaling out various requirements of the cloud-based mobile app due to the web service provider’s meter which runs at most of the time. Elastic scalability is provided by NuoDB at lots of transactions per second with less administration.

  1. Web-Scale Applications

Developers must get to know better beforehand about their applications release. It is possible for another major app better than Facebook. All the elastic-scale out is given to them by NuodB and they might mostly require integrated safety and awareness of SQL/ACID.

  1. Multi-Tenant Solutions

For hosting lots of databases there is a requirement for Internet Service Providers which is efficient while keeping all the customer’s database isolated from each other. True multi-tenancy is offered by NuoDB at cheap cost and has been deployed on lots of servers.

  1. Saas Solutions

There are lots of providers of SaaS and ISVs that are successful and have sharded, tuned and replicated making sure of high performance and zero downtime. There is no need for sharding, replication or various performance works in NuoDB.

  • Disadvantage of SQL over NuoDB?

SQL is regarded as a relation-based data model in the world of data and it mostly means for retrieving and changing the data. This is mostly used and has clauses, predicates, expressions, and queries in an SQL data management system for making it famous and user-friendly. This transactional data provides tough limitations like:

When Big Amount of Data is Used

  • For multi-table data graph, mostly incorrect SQLs are developed

  • Lots of your storage is occupied and therefore data repetition happens.

  • There is no possibility to use DML operations.

  • The view seems to be inactive because of the lack of a table.

  • There is no feature of elasticity present over here.

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Google’s Cloud Spanner

The beat launch of Cloud Spanner was declared today by Google and it is a new globally distributed database service for the purpose of mission applications. There are other cloud-based database services that are joined by Cloud Spannerlike Cloud SQL, Bigtable and the Cloud Datastore but with the main difference of providing developers the best relational databases and NoSQL databases and it is transactional with easier scalability. Cloud Spanner is another solution for developers who are striking the limits of cultural relational databases like PostgreSQL or MySQL.

Google usage of this version internally is the reason behind the name Cloud Spanner and a paper was published in the year 2012. In the year 2007, Google started working on Spanner just to search for an alternative to MySQL which ran lots of company products.

Spanner is the basis for various application of Google like Google Photos and many Google’s mission-critical applications. This same database service is made by Google to be available to outside developers with Cloud Spanner.

All the developers are to be assisted to take the knowledge in composing SQL-based applications and permit them to take that to a new database service that uses the SQL syntax and provides ACID transactions and apart from that there are other benefits of modern NoSQL database combined with the scalability kind and global network that Google needs to run its products.

  • Spanner is not a complaint of MySQL or ANSI SQL and there is no such plan

Moving workloads from MySQL is the target for Google’s Spanner and is the biggest interest and use case. Most of them felt bad about the lack of MySQL support both in the present and in the Spanner roadmap. There is a need for more pressure from MySQL to migrate or move a workload and for ensuring a performant implementation.

  • Full RDBMS functionalities are not offered by Cloud Spanner similar to referential integrity.

A parent or child relationship is needed by the Spanner when designing your data model to define at the table level. It is said that in other places this is by choice. There is no referential integrity performed on an automatic basis if you do not define tables as interleaved. If you later believe that you change the table into a child then you are going to have a drop or recreate the table.

  • The online schema does not offer cloud spanner for changing the keys.

Drop and replace of the table will be present in you and this happens when you need to change the PK of your table. This implies that you need to pause your workload and it means to take a downtime. And you need to understand why you want to change the table’s PL? In bold or all caps and red the spanner documentation is highlighted.

  • Index choosing is difficult when cloud spanning comes into the picture and it recommends using FORCE_INDEX directives in your code.

SQL operation is done from SQL to Google’s APIs and the efforts of the application programmer will have to be supported by data architects and they are people who are aware of both design around the limits of Spanner along with neglecting Spanner-specific anti-patterns which reduce performance.

This implies changing Pks to hashes and taking away auto-increment and correctly assigning parent/child data relationships as interleaved tables and interleaving needed indexes along with design time.

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SAP SOFTWARE SYSTEM

  • Define SAP ERP

For the purpose of making enterprise resource planning (ERP), a German multinational software company is used which is called as SAP. For managing business operations, organizations permit ERP software and usually means to suit modular applications for collecting and integrating data from various aspects of the business. For Erp software, there is only one provider called SAP. There are other providers like Microsoft, Oracle, Epicor, and Infor Orbis.

For the purpose of enterprise management, here is a basic overview of SAP’s modules implementation methods and here it stands against the competitors.

  • SAP’s Enterprise Resource Planning Modules

When neatly integrated ERP software comes into the picture, SAP becomes the prime leader and there are lots of departmental applications work symphonically. SAP offers industry-specific add-on solutions is beyond its basic models. There are lots of modules present in the SAP ERP and the main categories are:

  • Accounting:

Finance (FI)

Investment Management (IM)

Project Systems (PS)

Controlling (CO)

Financial Supply Chain Management (FSCM)

  • Logistics

Material Management (MM)

Sales and Distribution (SD)

Logistics Execution (LO)

Warehouse Management (WM)

Plant Maintenance (PM)

Quality Management (QM)

Production planning (PP)

Environment, Health, and Safety (EH&S)

  • Human Resources

Organization Management (HR-OM)

Payroll (HR-PY)

Training and Event Management (HR-TE)

Learning Solutions (HR-LSO)

Compensation (HR-CM)

Enterprise Compensation (HR-ECM)

Benefits (HR-BN)

Recruitment (HR-PB)

Loan (HR-LN)

Advance Business Application Programming (HR-ABAP)

  • Technology

Cross-Application (CA), includes classification systems and workflow

Basic Components (BC or BASIS)

Programming (ABAP)

Security and Authorizations

  • Other Modules (requiring separate installation)

Business Warehouse (BW)

Business Intelligence (BI)

International Demonstration and Education System (IDES)

Customer Relationship Management (CRM)

Master Data Management (MDM)

Supplier Relationship Management (SRM)

Exchange Infrastructure (XI)

Process Integration (PI)

Global Trade Services (GTS)

Strategic Enterprise Management (SEM)

Corporate Finance Management (CFM)

There are some modules in Finance and Investment Management and can be classified as Receivable or Accounts payable, Investment Support or Investment Orders. There are industry requirements and business operations for finding the modules actually needed. Sales and Distribution, finance, controlling, Human Resources, Material Management are few of the most significant sub-modules in SAP. Organizational needs are the basis for a client to buy the modules requirement. For instance, an SD, FI and MM modules can be bought by a client only without buying HR and CO modules.

  • SAP History

Five-ex employees of IBM developed SAP and it was developed in the year 1972 and is a small software company in Germany with just one client. Systems, Applications, and Products is the full form of SAP. The ultimate goal of its founders is to process the data when a user actually needs it, instead of overnight batches with reference to the earlier software. IBM’s punch-card data storage was changed to make their first product and it stores data on a mechanical basis and needed overnight processing. Imperial Chemical Industries German branch is the client of SAP and for them, they developed a real time payroll and punch-card system in the year 1972.

R/2 was the actual version of SAP’s ERP and named for its real-time architecture and two servers. After sometime it was name was changed to R/3 for three servers called as production server, application server and database server. The latest version of SAP was released in the year 2006, ECC6.0 and in the year 2013 an Enhancement Package (EHP7) was unveiled.

All department of organizations is handled by the ERP system called as SAP. An organizations’ Finance, Human Resource, Controlling, Research and many other departments are handled by SAP. A special industry-specific solution is present in SAP for almost various industries like Pharmaceuticals, manufacturing, Security, Insurance, Treas, Finance, etc.

There are lots of significant modules like SAP, SD, FICO, and HR. Finance and controlling respectively are controlled by Fi and CO. HR controls Human Resource departments and sales are controlled by SD. MM, SD, PS and HR modules are connected with FICO which is a base module.

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IBM DB2

Overview

An IBM’s database product called as DB2 is a Relational Database Management System. It is used for storing, retrieving, analyzing the data efficiently. With the assistance of object-oriented features and non-relational structures with XML, DB2 product is quite extended.

  • History

DB2 product has been developed by IBM originally for their specific platform. In the year 1990, it was considered to develop a Universal Database (UDB) DB2 Server for running various operating systems like UNIX, LINUX, and Windows.

  • Versions

The current version 10.5 is present in the IBM DB2 and it exhibits the features of BLU Acceleration and its code name is Kepler.

Here Are The Some Versions of DB2 Below:

3.4 Cobweb

8.1,8.2 Stinger

9.1 Viper

9.5 Viper 2

9.7 Cobra

9.8 Its added features with only pure scale

10.1 Galileo

  • Data Server Editions and Features

The requirement of needed features of DB2 is the basis for the organizations to choose an apt DB2 version. Here are few DB2 server editions and features:

  • Advanced Enterprise Server Edition and Enterprise Server Edition : Especially for mid-size to large-size business companies, this edition is developed. There are various platforms like Linux, UNIX, and Windows. Table partitioning High Availability Disaster Recovery (HARD) Materialized Query Table (MQTs) Multidimensional Clustering (MDC) Connection concentrator Pure.

  • Workgroup Server Edition (WSE) : For Workgroup or mid-size business organizations this is very much designed. With the help of this WSE, you can work with High Availability Disaster Recovery (HARD) Online Reorganization Pure XML Web Service Federation support DB2 Homogeneous Federations Homogeneous SQL replication Backup compression

  • Express C : All the capabilities of DB2 is offered by it at zero charges. On any physical or virtual systems it can run with any size of configuration.

  • Express Edition : Especially for entry-level and mid-size business organizations. It is a full-featured DB2 data server. It provides only a few services. Here are few edition that comes with- Web Service Federations DB2 homogeneous federations Homogeneous SQL Replications Backup compression.

  • Enterprise Developer Edition : Only single application developer is offered by it. It is useful for designing, building and prototyping the applications for deployment of various IBM server. For developing applications, the software cannot be used.

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Amazon SimpleDB

The developers are enabled with highly available and flexible NoSQL column database called Amazon SimpleDB for storing and querying structured data items through Web services requests. High availability and flexibility are offered by the design along with Amazon SimpleDB as it reduces the database administration burden.

Database as a service (DbaaS) offering is hosted by Amazon SimpleDB. An account can be set up by Amazon SimpleDB for use for storing and querying data items with the help of Web Services requests.

  • Amazon SimpleDB Offerings

Basic (included), which offers 24 x7 customers service.

Best practice guidance and an assured response time to incidents which is less than 12 hours are included by the developer.

API support and assured response time to incidents which is less than one hour are included in the business.

Direct access to a technical account manager is included by Enterprise infrastructure event management and assured response of incidents which is less than 15 minutes.

  • Amazon SimpleDB Features

For creating and storing multiple data sets, a simple Web Services interface is offered by Amazon SimpleDB by querying your data and returning the results.

Here are few highlights:

A subscriber is any application, software or script for making a call to the Amazon SimpleDB service. Each subscriber is identified by the AWS Access Key ID for billing and metering purposes.

A single Web service API call also called Amazon Simple DB Request and it’s associated data that the subscriber sends to the Amazon SimpleDB service to perform more than one operations.

Any results returned from the Amazon SimpleDB service is none other than Amazon SimpleDB Response to the subscriber after processing the request. Authentication success and failure are handled by the AWS platform.

For running a production database, Amazon SimpleDB makes you reduce the work needed to run a production database. For entering the information it is the best and low-touch data store about conditions or events, status updates, recurring activities, work flow processes and application states. These data logs are meant to be set and forgotten by Amazon SimpleDB and use them for things like tracking or monitoring, trend analysis, metering, auditing and archival or meeting requirements.

Online gaming is supported by Amazon SimpleDB apart from that. There are a high availability and scalability with a database which is free of administration for user and game data especially for developers of online games on any platform.

If there is a need to do any data comparison like GROUP BY or aggregate data or something more than simple storage and retrieval, Amazon SimpleDB is not about to work as well.

  • Amazon SimpleDB data types

Text Strings is the only way treated by all the data. You can organize your structured data by using Amazon SimpleDB in domains and you feed data into it and get data or run queries. Items described by attribute name-value pairs are present in the domain. Various data stored in Amazon SimpleDB is not indexed manually for fast and accurate retrieval.

  • Getting started with Amazon SimpleDB

It is a known fact that Amazon SimpleDB is not an open source and there is no licensed software for installing on a local server. Rather, you need to pay for what you use and there is no minimum fee required. The price depends on the region to establish your Amazon SimpleDB domain(s).

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Top Enterprise Database Systems

In the year 2017, here are few top enterprise database systems on market and this will help you find the apt solution that will work the best for you:

  • Oracle Database

In the year 1979, Oracle started its journey and was the first commercially present relational database management system (RDBMS). Enterprise database systems and Oracle’s name is quite similar and has unbreakable data delivery and tough corporate competition. The mainstay of this Fortune 500 company is powerful but complex database solutions.

Oracle 12c is the recent release of Oracle’s RDBMS. C means cloud and is reflective of Oracle’s work in spreading its enterprise RDBMS to enable firms for consolidating and managing databases like cloud services when needed through Oracle’s multitenant architecture and in-memory data processing capabilities.

  • Microsoft SQL Server

Explain more details about Microsoft but all other tech companies are exceeded profitably and SQL Server helped put it here. It is quite sure that Microsoft’s desktop operating system is everywhere but if a Microsoft Windows-based server is run by you are running it likely on SQL Server.

It is quite easy to use and is available and the windows operating is tight with integration and makes it a good choice for firms that take Mircosoft products for their enterprises. The latest release of SQL Server 2016 is promoted by Microsoft as the platform both on-premises and cloud databases and business intelligence solutions

In assisting enterprises built on mission-critical applications with high performance, Microsoft also helps SQL Server 2016 with in-memory security technology in OLTP, business intelligence, and analytics.

  • IBM DB2

The big into data centers is put by big blue with DB2. On Linux, UNIX, Windows, the latest release of DB2, DB2 11.1 actually runs. Its DB2 system has been pitted by IBM in a contest with Oracle’s through the International Technology Group and the results showed important cost savings for migrating to DB2 from Oracle.

  • SAP Sybase ASE

In the enterprise market after 25 years of improvements and success, Sybase is still regarded as a major force in its Adaptive Server Enterprise product. Although for few years its market share got reduced it is regarded as something important in the following generation transaction processing space which was owned by Sybase in 2010 and renamed as SAP Sybase ASE. There is also a good amount of support offered by Sybase behind the mobile enterprise by offering partnered solutions to the mobile device market.

  • PostgreSQL

This is regarded as an open-source object-relational management system and is also called as Postgres. Online gaming applications, data center automation suites, and domain registries are few attractive place for its residents. There are some big shots like Skype and Yahoo that it enjoys. There are various strange and tough places that it might deserve the moniker, especially in PostgreSQL. PostgreSQL 9.6.3 is the release of PostgreSQL currently in May 2017. There was an expectation of PostgreSQL 10 in the later part of 2017 and PostgreSQL 10 beta 2 is actually present for you now.

  • MariaDB Enterprise

It is a fully open source database system and all the codes are unveiled under LGPL, GPL, or BSD. MySQL RDBMS’s community-driven fork was started by MariaDB in 2009 and is led by the actual developers of MySQL who started the fork following concerns above MySQL’s acquisition by Oracle.

Recently the MariaDB has seen its fame at the expense of MySQL especially in its assistance by famous Linux distributions. The MySQL was downtrodden by Red Hat Enterprise Linux (RHEL) in the year 2013 and MariaDB were chosen instead of Linux by Fedora. The most attractive factor of MariaDB’s fame is its improved query optimization which enhances the efficiency of database more than MySQL.

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Differences Between Data Lakes and Datawarehouse

The main reason for writing this article is to project the difference between data lakes and data warehouses for helping you to know more about data management. Most of the data and analytics practitioners will understand the term. Let us see the main differences:

  • Data Lakes Retain All Data

While developing the data warehouse there is a need to invest a good time to analyze data sources and understand the business processes and profiling data. You will get a highly structured data model, especially for reporting. In this process, the major work is to identify the data to include and avoid. The main thing over here is to make decisions about the type of data to add and to reject in the warehouse. Normally in a report that is defined in the data is not referred for answering particular questions, it will be deleted from the warehouse. For simplifying the data model this is particularly done and also for protecting space on costly disk storage that is used for making the data warehouse performant.

  • Data Lakes Assists All Data Types

Normally the data warehouses consist of data taken from the transactional systems and are composed of quantitative metrics and they are defined by the attributes. Sensor data, web server logs, social network activity, text, and images are avoided and they are termed as Non-traditional data sources. It will quite difficult and expensive for consuming and storing the data. The non-traditional data types are approached by the data lake irrespective of source and structure in the data lake. Schema on reading vs the Schema on Write is the approach used in the data warehouse.

  • Data Lakes Support All Users

Here you can find 80% or lots of users are working. They want to obtain reports and check their performance metrics or slice in a spreadsheet daily. For these users, the data warehouse is actually ideal and it is quite structured and easy to use and understand and for answering these question it is built with some object.

The data is analyzed more on the next 10 percent. The source used over here is the data warehouse but often revert back to source systems to obtain the data that is not added to the warehouse and sometimes get the data from the external organization. Their new reports created are spread everywhere in the organization.

  • Data Lakes Adapt Easily to Modification

The important drawback of the data warehouse is its longer time consumptions for changing them. While developing there is a lot of time invested and obtain the warehouse’ structure correctly. It is a familiar fact that a good warehouse will be submissive to change but it will take a lot of time for the loading process and the work was done to make analysis and report easy.

For the data warehouse team, there are lots of business questions for adapting their system to respond them. The concept of self-service business intelligence is done by rapid answers. Since the entire data is present in its raw form and can be managed by someone else who needs it and the data can be explored by the users to go ahead of the structure of the warehouse in the novel ways and respond their queries.

  • Data Lakes Provide Rapid Insights

This difference has been got from the other four points and the reason is that data lakes contain various data and data types as it enables users to fetch their results on a rapid way when compared to the traditional data warehouse approach. Moreover, this early access to data arrives at a price. The data warehouse development team does the work and will not do work for some or other data sources needed for an analysis. There are lots of structured views of the data in the data lake that actually looks like what they have had earlier in the data warehouse.

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