Google Cloud SQL provides easier MySQL for all

Google Cloud SQL aims to provide easier MySQL for all

With the general availability of Google Cloud Platform’s latest database offerings — the second generation of Cloud SQL, Cloud Bigtable, and Cloud Datastore — Google is setting up a cloud database strategy founded on a basic truth of software: Don’t get in the customer’s way.

For an example, look no further than the new iteration of Cloud SQL, a hosted version of MySQL for Google Cloud Platform. MySQL is broadly used by cloud applications, and Google is trying to keep it fuss-free — no small feat for any piece of software, let alone a database notorious in its needs for tweaks to work well.

Most of the automation around MySQL in Cloud SQL involves items that should be automated anyway, such as updates, automatic scaling to meet demand, autofailover between zones, and backup/roll-back functionality. This automation all comes via a recent version of MySQL, 5.7, not via an earlier version that’s been heavily customized by Google to support these features.

The other new offerings, Cloud Datastore and Cloud Bigtable, are fully managed incarnations of NoSQL and HBase/Hadoop systems. These systems have fewer users than MySQL, but are likely used to store gobs more data than with MySQL. One of MySQL 5.7’s new features, support for JSON data, provides NoSQL-like functionality for existing MySQL users. But users who are truly serious about NoSQL are likely to do that work on a platform designed to support it from the ground up.

The most obvious competition for Cloud SQL is Amazon’s Aurora service. When reviewed by InfoWorld’s Martin Heller in October 2015, it supported a recent version of MySQL (5.6) and had many of the same self-healing and self-maintaining features as Cloud SQL. Where Google has a potential edge is in the overall simplicity of its platform — a source of pride in other areas, such as a far less sprawling and complex selection of virtual machine types.

Another competitor is Snowflake, the cloud data warehousing solution designed to require little user configuration or maintenance. Snowflake’s main drawback is that it’s a custom-build database, even if it is designed to be highly compatible with SQL conventions. Cloud SQL, by contrast, is simply MySQL, a familiar product with well-understood behaviors.

 

 

 

[Source:- IW]

SQL Server 2016 heads for release, but Linux version is still under wraps

Linux version of SQL Server 2016 still under wraps

SQL Server 2016, Microsoft’s newest database software, is set to become available on June 1 along with a no-cost, developers-only version.

With its new features and revised product editions, Microsoft is determined to expand SQL Server appeal to the largest possible number of customers running in a range of environments. But there’s still no word on the promised SQL Server for Linux, a version of the popular database that Microsoft is hoping will open SQL Server to an entirely new audience.

A broader SQL Server market awaits

Much of what’s new in SQL Server 2016 is aimed at roughly two classes of users: those doing their data collection and storage in the cloud (or moving to the cloud) and those doing analytics work that benefits from being performed in-memory. Features like Stretch Database will appeal to the former, as SQL Server tables can be expanded incrementally into Microsoft Azure — a more appealing option than a disruptive all-or-nothing migration.

Big data features include expanded capabilities for the Hekaton in-memory functions introduced in SQL Server 2014, plus in-memory columnstore functions for real-time analytics. And SQL Server’s close integration with the R language tools that Microsoft recently acquired opens up the database to a range of new applications from a thriving software ecosystem.

The forthcoming Linux version of SQL Server, though, is how Microsoft really plans to expand to an untapped market. And not just Linux users, but a specific kind of Linux user: those who use Oracle on Linux but are tired of Oracle’s unpredictable licensing. Oracle has been trying to change its tune, but there’s a lot to be said for being able to run SQL Server without also needing to run Windows.

Which versions and when?

Two big questions still remain about SQL Server for Linux. The first is when will it see the light of day; Microsoft hasn’t provided a timeframe yet. (A Microsoft spokesperson could provide no new comment.)

The second is what its pricing and SKUs will look like; will the feature set match what’s available on Windows or will it be a stripped-down version? Microsoft has versions of SQL Server to match most any workload or budget, from the free-to-use Express edition to the full-blown Enterprise variety.

With SQL Server 2014 — and now with 2016 as well — the company introduced a free-to-use developer version of the Enterprise SKU intended solely for dev and testing work. It’s unclear whether SQL Server on Linux will also include a developer version or only include editions specifically for commercial use.

Whatever happens with SQL Server on Linux, Microsoft’s already making aggressive efforts to woo Oracle users into its camp. The company has a limited-time Oracle-to-SQL-Server migration offer, where Microsoft Software Assurance customers can swap Oracle licenses for SQL Server licenses at no cost. It’ll be intriguing if a similar offer pops up again after Microsoft releases SQL Server for Linux.

 

 
[Source:- Infoworld]

Apache Spark powers live SQL analytics in SnappyData

Apache Spark powers live SQL analytics in SnappyData

The team behind Pivotal’s GemFire in-memory transactional data store recently unveiled a new database solution powered by GemFire and Apache Spark, called SnappyData.

SnappyData is another recent example of Spark employed as a component in a larger database solution, with or without other pieces from Apache Hadoop.

Snap and spark

SnappyData — the name of both the new database and the organization producing it — was built to span two worlds. It uses the Apache Spark in-memory data-analytics engine so that it can perform live SQL analytics on both static data sets and streams. Queries against SnappyData can be written as conventional SQL or as Spark abstractions, so existing work done in both paradigms can be reused, alone or together, on the same data.

To store and retrieve the data, SnappyData has a distributed data store called Snappy-Store, derived from a variant of Pivotal’s GemFire technology. It works as either its own data store or as a sort of asynchronous write-back cache to other data sources, such as Hadoop/HDFS. This implies that existing data sets could be accessed through SnappyData without having to be formally migrated.

SnappyData also tries to offer novel solutions to problems that can arise when using streaming data. For instance, if there’s too much data coming through to get a real-time response to a query in a timely fashion, SnappyData uses approximate query processing (AQP) or a method of sampling streaming data to generate an answer.

The results are less exact than operating on the entire data set, and AQP isn’t available for every kind of query. That said, AQP queries are intended to be faster to run and are less demanding of CPU and memory than working on the full data set.

One among many

This isn’t the first time Spark has been used at the heart of a data analysis solution that covers both OLTP and OLAP workloads. In-memory database system Splice Machine was originally built on top of Hadoop components and leveraged them to scale out and be able to run both OLTP and OLAP jobs under the same hood. Version 2.0 of that product added Spark as an OLAP processing engine.

Where SnappyData diverges from Splice Machine, though, is in how Spark is used. SnappyData claims it’s extending Spark Streaming in various manners, such as allowing streams to be manipulated and queried as though they were tables, including operations like joins.

SnappyData also seems like a good environment to leverage changes that are slated for Apache Spark in the near term. For instance, Spark 2.0, scheduled to come out later this year, will heavily rework how Spark handles memory management and introduce changes to its streaming system that make it easier to pull down streaming data.

 
[Source:- Infoworld]

 

Microsoft SQL Server 2016 finally gets a release date

Microsoft SQL Server 2016 finally gets a release date

Database fans, start your clocks: Microsoft announced Monday that its new version of SQL Server will be out of beta and ready for commercial release on June 1.

The news means that companies waiting to pick up SQL Server 2016 until its general availability can start planning their adoption.

SQL Server 2016 comes with a suite of new features over its predecessor, including a new Stretch Database function that allows users to store some of their data in a database on-premises and send infrequently used  data to Microsoft’s Azure cloud. An application connected to a database using that feature can still see all the data from different sources, though.

Another marquee feature is the new Always Encrypted function, which makes it possible for users to encrypt data at the column level both at rest and in memory. That’s still only scratching the surface of the software, which also supports creating mobile business intelligence dashboards and new functionality for big data applications.

SQL Server 2016 will come in four editions: Enterprise, Standard, Developer and Express. The latter two will be available for free, similar to what Microsoft offered with SQL Server 2014.

In addition to its on-premises release, Microsoft will also have a virtual machine available on June 1 through its Azure cloud platform that will make it easy for companies to deploy SQL Server 2016 in the cloud.

Many of the new features in SQL Server 2016 like Always Encrypted and Stretch Database are already available in Microsoft’s Azure SQL Database managed service, but the virtual machine will be useful for companies that prefer to manage their own database infrastructure or that plan to roll out SQL Server 2016 on premises and want to test it in the cloud.

All of this comes a few months after Microsoft shocked the world by announcing that it would also release SQL Server on Linux in the future. That’s a powerful sign of Microsoft’s strategy of making its tools available to users on a wide variety of platforms, even those that the company doesn’t control.

 

 

[Source:- Infoworld]

CrateDB packs NoSQL flexibility, SQL familiarity

CrateDB packs NoSQL flexibility, SQL familiarity

CrateDB, an open source, clustered database designed for missions like fast text search and analytics, released its first full 1.0 version last week after three years in development.

It’s built upon several existing open source technologies — Elasticsearch and Lucene, for instance — but no direct knowledge of them is needed to deploy it, as CrateDB offers more than a repackaging of those products.

The database caught the attention of InfoWorld’s Peter Wayner back in 2015 because it promised “a search engine like [Apache] Lucene [and ‘its larger, scalable, and distributed cousin Elasticsearch’], but with the structure and querying ease of SQL.”

The idea is to provide more than a full-text search system. CrateDB’s use cases include big data analytics and scalable aggregations across large data sets. It allows querying via standard ANSI SQL, but it uses a distributed, horizontally scalable architecture, so that any number of nodes can be spun up and run side by side with minimal work.

CrateDB gets two major advantages from the NoSQL side. One is support for unstructured data via JSON documents and BLOB storage, with JSON data queryable through SQL as well. Another is support for high-speed writing, to make the database a suitable target for high-speed data ingestion a la Hadoop.

But CrateDB’s biggest draw may be the setup process and the overall level of get-in-and-go usability. The only prerequisite is Java 8, or you can use Docker to run a provided container image. Nodes automatically discover each other as long as they’re on a network that supports multicast. The web UI can bootstrap a cluster with sample data (courtesy of Twitter), and the command-line shell uses conventional SQL syntax for inserting and querying data. Also included is support for PostgreSQL’s wire protocol, although any actual SQL commands sent through it need to adhere to CrateDB’s implementation of SQL.

CrateDB’s one of a flood of recent database products that all address specific issues that have sprung up: scalability, resiliency, mixing modalities (NoSQL vs. SQL, document vs. graph), high-speed writes, and so on. The philosophy behind such products generally runs like this: Existing solutions are too old, hidebound, or legacy-oriented to solve current and future problems, so we need a clean slate. The trick will be to see whether the benefits of the clean slate outweigh the difficulties of moving to it — hence, CrateDB’s emphasis on usability and quick starts.

 

[Source:- Infoworld]

 

91% off Microsoft Certified Solutions Associate: SQL Server Certification Bundle – Deal Alert

sql course

Whether or not you’ve dabbled with queries or databases, earning a MCSA certification will attract the eyes and wallets of company execs across the states and beyond. SQL is a go-to software for implementing data warehouses, as well as efficiently managing massive amounts of data. In this bundle, currently discounted 91%, you’ll access three courses:

  • Microsoft 70-461: Querying Microsoft SQL Server 2012
  • Microsoft 70-462: Administering Microsoft SQL Server 2012 Databases
  • Microsoft 70-463: Implementing A Data Warehouse With Microsoft SQL Server 2012

This $438 course bundle is available, for a limited time, for just $35.99. Learn more about this bundle, the courses included, the instructor, and how to purchase.

 

 

[Source:- Infoworld]

 

Microsoft rolls out SQL Server 2016 with a special deal to woo Oracle customers

Microsoft has released SQL Server 2016.

The next version of Microsoft’s SQL Server relational database management system is now available, and along with it comes a special offer designed specifically to woo Oracle customers.

Until the end of this month, Oracle users can migrate their databases to SQL Server 2016 and receive the necessary licenses for free with a subscription to Microsoft’s Software Assurance maintenance program.

Microsoft announced the June 1 release date for SQL Server 2016 early last month. Among the more notable enhancements it brings are updateable, in-memory column stores and advanced analytics. As a result, applications can now deploy sophisticated analytics and machine learning models within the database at performance levels as much as 100 times faster than what they’d be outside it, Microsoft said.

The software’s new Always Encrypted feature helps protect data at rest and in memory, while Stretch Database aims to reduce storage costs while keeping data available for querying in Microsoft’s Azure cloud. A new Polybase tool allows you to run queries on external data in Hadoop or Azure blob storage.

Also included are JSON support, “significantly faster” geospatial query support, a feature called Temporal Tables for “traveling back in time” and a Query Store for ensuring performance consistency.

SQL Server 2016 features were first released in Microsoft Azure and stress-tested through more than 1.7 million Azure SQL DB databases. The software comes in Enterprise and Standard editions along with free Developer and Express versions.

Support for SQL Server 2005 ended in April.

Though Wednesday’s announcement didn’t mention it, Microsoft previously said it’s planning to bring SQL Server to Linux. That version is now due to be released in the middle of next year, Microsoft said.

 

[Source:- Infoworld]

 

Azure brings SQL Server Analysis Services to the cloud

Azure brings SQL Server Analysis Services to the cloud

SQL Server Analysis Services, one of the key features of Microsoft’s relational database enterprise offering, is going to the cloud. The company announced Tuesday that it’s launching the public beta of Azure Analysis Services, which gives users cloud-based access to semantic data modeling tools.

The news is part of a host of announcements the company is making at the Professional Association for SQL Server Summit in Seattle this week. On top of the new cloud service, Microsoft also released new tools for migrating to the latest version of SQL Server and an expanded free trial for Azure SQL Data Warehouse. On the hardware side, the company revealed new reference architecture for using SQL Server 2016 with active data sets of up to 145TB.

The actions are all part of Microsoft’s continued investment in the company’s relational database product at a time when it’s trying to get customers to move to its cloud.

Azure Analysis Services is designed to help companies get the benefits of cloud processing for semantic data modeling, while still being able to glean insights from data that’s stored either on-premises or in the public cloud. It’s compatible with databases like SQL Server, Azure SQL Database, Azure SQL Data Warehouse, Oracle and Teradata. Customers that already use SQL Server Analysis Services in their private data centers can take the models from that deployment and move them to Azure, too.

One of the key benefits to using Azure Analysis Services is that it’s a fully managed service. Microsoft deals with the work of figuring out the compute resources underpinning the functionality, and users can just focus on the data.

Like its on-premises predecessor, Azure Analysis Services integrates with Microsoft’s Power BI data visualization tools, providing additional modeling capabilities that go beyond what that service can offer. Azure AS can also connect to other business intelligence software, like Tableau.

Microsoft also is making it easier to migrate from an older version of its database software to SQL Server 2016.  To help companies evaluate the difference between their old version of SQL Server and the latest release, Microsoft has launched the  Database Experimentation Assistant.

Customers can use the assistant to run experiments across different versions of the software, so they can see what if any benefits they’ll get out of the upgrade process while also helping to reduce risk. The Data Migration Assistant, which is supposed to help move workloads, is also being upgraded.

For companies that have large amounts of data they want to store in a cloud database, Microsoft is offering an expanded free trial of Azure SQL Data Warehouse. Users can sign up starting on Tuesday, and get a free month of use. Those customers who want to give it a shot will have to move quickly, though: Microsoft is only taking trial sign-ups until December 31.

Microsoft Corporate Vice President Joseph Sirosh said in an interview that the change to the Azure SQL Data Warehouse trial was necessary because setting up the system to work with actual data warehouse workloads would blow through the typical Azure free trial. Giving people additional capacity to work with should let them have more of an opportunity to test the service before committing to a large deployment.

All of this SQL news comes a little more than a month before AWS Re:Invent, Amazon’s big cloud conference in Las Vegas. It’s likely that we’ll see Amazon unveil some new database products at that event, continuing the ongoing cycle of competition among database vendors in the cloud.

 

 

[Source:- IW]

Microsoft: SQL Server for Linux is the real deal

Microsoft: SQL Server for Linux is the real deal

Those who wondered what it would be like to run Microsoft SQL Server on Linux now have an answer. Microsoft has released the first public preview of the long-promised product.

Microsoft also wants to make clear this isn’t a “SQL Server Lite” for those satisfied with a reduced feature set. Microsoft has a four-point plan to make this happen.

First is through broad support for all major enterprise-grade Linux editions: Red Hat Enterprise Linux, Ubuntu Linux, and soon Suse Linux Enterprise Server. “Support” means behaving like other Linux applications on the distributions, not requiring a Microsoft-only methodology for installing or running the app. An introductory video depicts SQL Server installed on RHEL through the system’s yum package manager, and a white paper describes launching SQL Server’s services via systemd.

Second, Microsoft promises the full set of SQL Server 2016’s features for Linux users—not only support for the T-SQL command set, but high-end items like in-memory OLTP, always-on encryption, and row-level security. It will be a first-class citizen on Linux, as SQL Server has been on Windows itself.

Third is Linux support for the tooling around SQL Server—not SQL Server Management Studio alone, but also the Migration Assistant for relocating workloads to Linux systems and the sqlps PowerShell module. This last item is in line with a possibility introduced when PowerShell was initially open-sourced: Once ported to Linux, it would become part of the support structure for other big-name Microsoft applications as they, too, showed up on the OS. That’s now happening.

By bringing SQL Server to Linux, Microsoft can compete more directly with Oracle, which has long provided its product on Linux. Oracle may be blunting the effects of the strategy by shifting customers toward a cloud-based service model, but any gains are likely to be hard-won.

The other, immediate benefit is to provide Microsoft customers with more places to run SQL Server. Enterprises have historically run mixes of Linux and Windows systems, and SQL Server on Linux will let them shave the costs of running some infrastructure.

Most of all, Microsoft is striving to prove a Microsoft shop can lose little, and preferably nothing, by making a switch—and a new shop eyeing SQL Server has fewer reasons to opt for a competing database that’s Linux-first.

 

 

 

[Source:- Infoworld]

CrateDB packs NoSQL flexibility, SQL familiarity

CrateDB packs NoSQL flexibility, SQL familiarity

CrateDB, an open source, clustered database designed for missions like fast text search and analytics, released its first full 1.0 version last week after three years in development.

It’s built upon several existing open source technologies — Elasticsearch and Lucene, for instance — but no direct knowledge of them is needed to deploy it, as CrateDB offers more than a repackaging of those products.

The database caught the attention of InfoWorld’s Peter Wayner back in 2015 because it promised “a search engine like [Apache] Lucene [and ‘its larger, scalable, and distributed cousin Elasticsearch’], but with the structure and querying ease of SQL.”

The idea is to provide more than a full-text search system. CrateDB’s use cases include big data analytics and scalable aggregations across large data sets. It allows querying via standard ANSI SQL, but it uses a distributed, horizontally scalable architecture, so that any number of nodes can be spun up and run side by side with minimal work.

CrateDB gets two major advantages from the NoSQL side. One is support for unstructured data via JSON documents and BLOB storage, with JSON data queryable through SQL as well. Another is support for high-speed writing, to make the database a suitable target for high-speed data ingestion a la Hadoop.

But CrateDB’s biggest draw may be the setup process and the overall level of get-in-and-go usability. The only prerequisite is Java 8, or you can use Docker to run a provided container image. Nodes automatically discover each other as long as they’re on a network that supports multicast. The web UI can bootstrap a cluster with sample data (courtesy of Twitter), and the command-line shell uses conventional SQL syntax for inserting and querying data. Also included is support for PostgreSQL’s wire protocol, although any actual SQL commands sent through it need to adhere to CrateDB’s implementation of SQL.

CrateDB’s one of a flood of recent database products that all address specific issues that have sprung up: scalability, resiliency, mixing modalities (NoSQL vs. SQL, document vs. graph), high-speed writes, and so on. The philosophy behind such products generally runs like this: Existing solutions are too old, hidebound, or legacy-oriented to solve current and future problems, so we need a clean slate. The trick will be to see whether the benefits of the clean slate outweigh the difficulties of moving to it — hence, CrateDB’s emphasis on usability and quick starts.

 

 

[Source:- Infoworld]