Cassandra is a NoSQL database management system, designed to handle very large amounts of data spread out across many commodity servers while providing a highly available service with no single point of failure.

Cassandra has Hadoop integration, with MapReduce support. There is support also for Apache Pig and Apache Hive.

CQL (Cassandra Query Language) was introduced, an SQL-like alternative to the traditional RPC interface. Language drivers are available for Java (JDBC) and Python (DBAPI2).

Cassandra is in use at Netflix, Twitter, Urban Airship, Constant Contact, Reddit, Cisco, OpenX, Digg, CloudKick, Ooyala, and more companies that have large, active data sets. The largest known Cassandra cluster has over 300 TB of data in over 400 machines.

http://cassandra.apache.org/

Today Teradata leads the industry not only in active data warehousing technology that provides a single view of the enterprise in real time, but also in business intelligence analytics that help you use data in imaginative new ways to gain maximum value.

We offer a powerful suite of business intelligence technology platforms and solutions, a wide range of data access and management applications and robust data mining capabilities.
Regardless of the size of your organization or the complexity of your analytic needs, a Teradata solution can generate actionable business intelligence and help you achieve a competitive edge.

With the strength of the industry’s largest and most experienced force of consultants, Teradata will partner with you to effectively design, implement and maintain your system and train your staff. That's our end-to-end data warehousing solution.

Teradata was named “one of the world’s most ethical companies” by The Ethisphere Institute.

http://www.teradata.com

U.S. and Canada
1-866-548-8348

For International Callers:
(937) 242-4030

World Headquarters
10000 Innovation Drive
Dayton, OH 45342

Greenplum is a big data analytics company driving the future of Big Data analytics with breakthrough products that harness the skills of data science teams to help global organizations realize the full promise of business agility and become data-driven, predictive enterprises.

Greenplum Unified Analytics Platform (UAP) combines the co-processing of structured and unstructured data with a productivity engine that enables collaboration among your data science team. Greenplum UAP includes Greenplum Database, Greenplum HD, and Greenplum Chorus.

Greenplum has over 500 customers, including Silver Spring Networks, Zions Bancorporation, Reliance Communications, NYSE Euronext, Bakrie Telecom, Orbitz, Havas Digital, China Unicom, ClickFox, Frank Templeton Investments and Tagged.

http://www.greenplum.com/

Benefits of Data Virtualization

Data virtualization is the process of offering data consumers a data access interface that hides the technical aspects of stored data, such as location, storage structure, API, access language, and
storage technology. Consuming applications may include: business intelligence, analytics, CRM, enterprise resource planning, and more across both cloud computing platforms and on-premises.

Data Virtualization Benefits:

● Decision makers gain fast access to reliable information
● Improve operational efficiency - flexibility and agility of integration due to the short cycle creation of virtual data stores without the need to touch underlying sources
● Improved data quality due to a reduction in physical copies
● Improved usage through creation of subject-oriented, business-friendly data objects
● Increases revenues
● Lowers costs
● Reduces risks

Data virtualization abstracts, transforms, federates and delivers data from a variety of sources and presents itself as a single access point to a consumer regardless of the physical location or nature
of the various data sources.

Data virtualization is based on the premise of the abstraction of data contained within a variety of data sources (databases, applications, file repositories, websites, data services vendors, etc.) for the purpose of providing a single-point access to the data and its architecture is based on a shared semantic abstraction layer as opposed to limited visibility semantic metadata confined to a single
data source.

Data Virtualization software is an enabling technology which provides the following capabilities:

• Abstraction – Abstract data the technical aspects of stored data, such as location, storage structure, API, access language, and storage technology.

• Virtualized Data Access – Connect to different data sources and make them accessible from one logical place

• Transformation / Integration – Transform, improve quality, and integrate data based on need across multiple sources

• Data Federation – Combine results sets from across multiple source systems.

• Flexible Data Delivery – Publish result sets as views and/or data services executed by consuming application or users when requested In delivering these capabilities, data virtualization also addresses requirements for data security, data quality, data governance, query optimization, caching, etc. Data virtualization software includes functions for development, operation and management.

http://www.rosebt.com/uploads/8/1/8/1/8181762/benefitsofdatavirtualization.pdf

Platfora makes the data that lives inside Hadoop clusters understandable and easier to use.

We bring business intelligence into the 21st century, giving business analysts the intuitive and richly interactive tools to explore and produce business insights from massive and rapidly evolving datasets.

Whether a company has Gigabytes, Terabytes or Petabytes of data, our platform eliminates the need for traditional data warehouses, ETL tools and the legacy BI products of the past. We replace complexity and scaling pain with simplicity and beauty.

PLATFORA’S BREAKTHROUGH SOLUTION is a combination of server technology, user experience innovation, and data science.

Our platform works with existing Hadoop clusters (Cloudera, MapR, Amazon EMR, etc.), and automatically turns the questions of business users into Hadoop jobs that synthesize and distill Hadoop datasets into dimensional and predictive dashboards, reports and insights.

The system intelligently drives Hadoop to create and maintain ‘work products’ — highly compressed partial results that are refined at the click of a button to achieve subsecond report delivery, analytics overlay, and drilldown performance.

http://www.platfora.com

100 S Ellsworth Ave, Suite 400
San Mateo, CA, 94401
650-918-1100

DataSift is the world's most powerful and scalable platform for managing large volumes of information from a variety of social data sources.

Social Data is more complicated to process and analyze because it is unstructured. DataSift's platform has been built specifically to process large volumes of this unstructured data and derive value from it.

DataSift lets you access the full Twitter firehose in a cost-effective way. Pick between pay-as-you-go and subscription models, so you pay just for the Tweets that you use.

DataSift was architected to handle large volumes of real-time data and immense numbers of sophisticated queries. This infrastructure supports billions of interactions and queries with regular response times of less than 200 ms.

http://datasift.com/

MongoDB is a scalable, high-performance, open source NoSQL database system. Written in C++

Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.

http://www.mongodb.org

Hadapt offers a Hadoop-based adaptive analytical platform for performing complex analytics on structured and unstructured data.

The Hadapt Adaptive Analytic Platform is the first big data platform to combine the benefits of Apache Hadoop and relational DBMS technology into a single system for applications that rely on multi-structured data analytics.

Hadapt was designed for the cloud, and is optimized for virtualized environments. In addition to providing the full power of MapReduce, Hadapt offers enhanced SQL support and the ability to work with all of your data within one platform.

http://www.hadapt.com

614 Massachusetts Ave.
4th Floor
Cambridge, MA 02139
(617) 539-6110
info@hadapt.com

Hadoop has both good and bad points. It is one tool among many and is not the right tool for every organization.

Hadoop has a high latency (long delay), which makes it bad for traditional business intelligence functions that require a low latency (small delay). It also comes with a steep learning curve and a workload that can significantly vary.

Hadoop does some things really well: analytical capabilities, support for ad-hoc queries on conventional databases, high degree of processing complexity, support for high volumes of unstructured data.

A better way to view Hadoop is to add and integrate Hadoop to the traditional data warehouse / BI systems, embracing it as a companion technology.

Hybrid RDBMS Systems Now Coined NewSQL Databases

When you look at the evolution of NoSQL it has primary evolved to solve specific problems that were difficult, not impossible, to solve using a traditional RDBMS. In other words, NoSQL became perhaps a "better" or "different" way to solve a problem. A lot of NoSQL solutions achieve their scalability by choosing to make compromises on things like consistency and transactions.

But what if you didn't want to compromise? What if you wanted scalability and things like ACID compliant transactions? Well a new crop of database startups started to emerge. Solutions like VoltDB, Clustrix and ScaleDB. Essentially they were a hybrid database offering a traditional RDBMS that could scale. Well now that group of databases have a new name, NewSQL!

The 451Group published a blog post in which they described what the term meant along with the players they felt fit within the group. Here's what the had to say about the term:

“NewSQL” is our shorthand for the various new scalable/high performance SQL database vendors. We have previously referred to these products as ‘ScalableSQL’ to differentiate them from the incumbent relational database products. Since this implies horizontal scalability, which is not necessarily a feature of all the products, we adopted the term ‘NewSQL’ in the new report.

The reaction so far by many of the companies included in the group has been extremely positive. In the end it's just a name, a way to categorize a group of similar solutions. It does bring a sense of legitimacy to the product group, as well as, a name to rally around as these solutions grow. And so the NewSQL era begins!

Luca Garuilli provides a slide presentation about using OrientDB as the primary data store for a web application.

Couple of interesting facts from the presentation:

100% compliant with TinkerPop's Blueprints
Multiple run modes i.e. embedded, in-memory, client/server
Supports transactions
Supports SQL queries

http://www.slideshare.net/lvca/orientdb-nosqlday

Citrusleaf is a NoSQL database that uniquely delivers reliability, linear scalability and exceptional performance for high volume, data intensive, web-scale and mobile businesses.

Citrusleaf provides the following:

Non-Stop Transactions
ACID (Atomic, Consistent, Isolated, Durable)
Immediate consistency
Automated clustering / Shared nothing
Flexible data storage supporting both Flash/SSD and rotational disk
Balanced Read/Writes with high throughput (200K+ TPS per node) and low latency (sub millisecond)
Support for billions of objects and terabytes of data

http://citrusleaf.net

+1 650-336-5323 (336-LEAF)
info@citrusleaf.com

Citrusleaf, Inc.
2525 Charleston Road
Mountain View, CA 94043

Cross Datacenter Replication Datasheet

http://citrusleaf.com/_docs/Citrusleaf_XDR_Datasheet.pdf

We are now getting disruption in the database market.

The two primary DBMS architectures are shared-nothing and shared-disk. Shared-nothing databases split or partition the data so that each database server exclusively processes and maintains its own piece of the database. Shared-disk is analogous to a single large trough of data, where any number of database nodes can process any portion of that data. Based upon traditional computing constraints, the shared-nothing architecture has been the price-performance leader.

That is now changing. The shared-nothing DBMS architecture gained widespread adoption on the basis of performance and cost advantages that no longer exist.

Shared storage, with the help of extremely fast interconnects, now
delivers data to the CPU several times faster than a local disk.

Cloud computing economics (leveraging the power of multi-tenancy) delivers extremely fast shared storage at a dramatically reduced cost.

Virtualization then compounds these advantages by enabling users to scale elastically and to pay only for the resources they use. The cost/performance advantages have decisively shifted in favor of the
shared-disk DBMS.

It was just a matter of time before the shared-disk DBMS established dominance in the cloud.

We are now seeing some significant disruption in the database landscape for enterprises and private clouds as well.

About time!

Karmasphere is a Big Data Intelligence Software company bringing Apache Hadoop power to the desktop.

The first step in analyzing Big Data is to connect to your Hadoop cluster and distribution – not an easy task if you are an analyst business user and all you have is a Linux prompt. Karmasphere Analyst lets you connect to any data on any Hadoop cluster, in a private data center, or private or public cloud, even behind firewalls from your Windows, MacOS or Linux desktop. We make it look as if it you were working on your local file system, all from a unified graphical interface with wizards and point-and click features.

The second step in analyzing Big Data is to assemble a variety of files and formats containing large volumes of data so that they can be explored for insight. The goal is to work on all the raw data and all its detail so that discoveries are not limited to aggregations and predefined structures and functions as in the traditional business intelligence world. Karmasphere Analyst guides the user with wizards to gather, organize and prepare any kind of raw data on-the-fly and then create Hive tables in preparation for analytics. This bypasses the lengthy aggregation and modeling steps usually taken to prepare business intelligence data warehouses.

The third A for Big Data Analytics is the analyze phase. This is when the analyst role changes to data miner and discoverer, navigating through the raw data to find the patterns, trends and insights that can transform the business. With Karmasphere Analyst, the data professional performs iterative ad hoc queries with the SQL-like Hive query language and interactive formatting, filtering, sorting and charting wizards to visualize the results in different ways. Over 150 predefined functions can be used in queries or you can add your own analytic functions. Once insight is discovered, the path the analyst took to that learning is retained so that it can be repeated and operationalized.

In order for the insights attained from Big Data to transform your business they must find their way into the hands of other individuals or integrated into business processes and applications. So the final phase for the Big Data analyst is to make sure insights incite action within the business. Karmasphere Analyst provides facilities for the business to “Act” on the Big Data insights created by the data professional. Results can be published and shared with other users and applications, and intellectual capital can be retained, shared, and operationalized. For example Karmasphere Analyst can send insights to enterprise data warehouses, Excel, Tableau, or other reporting and Business Intelligence tools.

https://karmasphere.com

19200 Stevens Creek Blvd., Suite 130
Cupertino, CA 95014
650.292.6100

VoltDB is an in-memory, fast NewSQL database system. It is specifically designed to run on modern scale-out architectures - fast, inexpensive servers connected via high-speed data networks.

VoltDB is aimed at a new generation of database applications – real-time feeds, sensor-driven data streams, micro-transactions, low-latency trading systems – requiring database throughput that can reach millions of operations per second. What’s more, the applications that use this data must scale on demand, provide flawless fault tolerance and enable real-time visibility into the data that drives business value.

VoltDB is more than an ultra-fast database. All product distributions come complete with developer productivity tools, sample apps and reference implementations to get your project off the ground quickly. And pre-packaged images for Amazon EC2 and VMware allow to try VoltDB without making significant infrastructure investments.

http://voltdb.com

6 Fortune Drive
Billerica, MA 01821 USA
978.528.4660
info@voltdb.com

MemSQL places data into memory and translates SQL into C++ for the utmost optimization in query execution. This enables MemSQL to write and read data at incredible speeds, and by offering a relational interface, you can unify the data you’d normally store in a short-lived medium—cache or key-value store—and place it directly into a database along with your existing data.

Get rid of custom code and caches that slow down your engineering teams.

MemSQL is the fastest way to ingest large volumes of data while simultaneously analyzing that data in real time. With the power to arrive at answers and actionable insights in seconds, you can adapt and adjust your business processes in concert with fluctuating conditions.

http://memsql.com

380 10th St, Ste 25
San Francisco, CA 94103
info@memsql.com

SpaceCurve geospatial-temporal database and graph analysis tools enable application developers and organizations to leverage the real-time models required for more powerful geospatial and other classes of applications and to extend existing applications.

SpaceCurve stores, manipulates and analyzes large quantities of geospatial, temporal, sensor network and social graph data in real time to empower a new class of applications, and extend existing applications in new ways.

SpaceCurve will deliver instantaneous intelligence for location-based services, commodities, defense, emergency services and other markets.

The company is developing cloud-based Big Data solutions that continuously store and immediately analyze massive amounts of multidimensional geospatial, temporal, sensor network and social graph data.

http://spacecurve.com
info@spacecurve.com

101 Yesler Way
Suite 507
Seattle, WA 98104

Bloggers like you are very few on World Wide Web and I am happy to found you. It’s like finding a pearl in the sea, tough but fruitful. Best wishes and regards.