CLOUD-BASED DATABASE GLOBAL MARKET 2017- SALESFORCE, CASSANDRA, SAP, COUCHBASE, MONGODB AND TERADATA

Global Cloud-based Database Research Report serves as a comprehensive guide to provide the latest Cloud-based Database industry trends like the growth opportunities, Cloud-based Database market size, product launch events and market drivers. This report offers the competitive landscape study of Cloud-based Database based on key manufacturers, market presence in various regions and Cloud-based Database market revenue. Global Cloud-based Database market is foreseen to experience tremendous growth due to technological advancements and innovations in the Cloud-based Database product. All the relevant details like product type, Cloud-based Database manufacturing cost, market scope, Cloud-based Database applications are evaluated at depth in this report. This report presents the past, present and forecast Cloud-based Database market information like the market size, Cloud-based Database growth rate, emerging sectors, Cloud-based Database revenue and consumer volume. Analysis of Cloud-based Database market statistics, market competition, Cloud-based Database production capacity, and utilization ratio will be useful to all the Cloud-based Database market aspirants. Global Cloud-based Database report analyses provide the Cloud-based Database industry view based on company profile of key Cloud-based Database players, their sales revenue, Cloud-based Database business strategies and market gain. The Cloud-based Database industry is sited to see a dynamic growth due to changing consumer demand, Cloud-based Database import/export scenario and analysis of Cloud-based Database emerging segments. This report presents the vital company details in the form of graph and tables which will offer a comprehensive view of Cloud-based Database industry. The analysis of Cloud-based Database growth opportunities, region-based study, and Cloud-based Database investment feasibility study will lead to accumulation of revenue. All the Cloud-based Database marketing strategies, business tactics, and forecast Cloud-based Database market trends will help the readers in identifying the Cloud-based Database growth factors. Do Enquiry for Cloud-based Database report here: http://emarketresearch.us/global-cloud-based-database-market-2017-2022/#Inquiry-Before-Buying Global Cloud-based Database report is segmented as follows: Global Cloud-based Database Market segmentation based on regions: This portion elaborates the major Cloud-based Database producing regions like North America, Europe, Asia-Pacific, Latin America, Africa, and Middle-East regions. Furtherly, the key countries involved in Cloud-based Database industry like United States, Mexico, Israel, Japan, China, Canada, Korea, India, Germany, UK, France, Russia, Italy, and Southeastern countries are covered. Global Cloud-based Database Market segmentation based on Manufacturers: This portion evaluates the Cloud-based Database market based on top manufacturers, their company details, sales volume, region, supply/demand scenario and Cloud-based Database development trends. Leading #Cloud -based #Database players are @Salesforce, @Cassandra, @IBM, @Google, @Alibaba, @MongoDB, @Rackspace Hosting, @Oracle, @AmazonWebServices, @Microsoft, @Tencent, @SAP, @Teradata and @Couchbase. Global Cloud-based Database Market segmentation based on product type: This portion cuts Cloud-based Database market into #NoSQL Database and #SQL Database. Also, lists all the Cloud-based Database product types based on classification, description, definiton, Cloud-based Database product scope, and consumer demand. Cloud-based Database Market segmentation based on product application: This portion divides Cloud-based Database market into Large Enterprises and Small and Medium Business. Wide-spread product applications can be attributed to the technological advancement and innovations taking place in Cloud-based Database sector.

http://publicistreport.com/technology-and-media/cloud-based-database-global-market-2017-salesforce-cassandra-sap-couchbase-mongodb-teradata.html

Despite big losses and big competition, database firm MongoDB files for an IPO

New York City-based database company MongoDB Inc. today formally announced its plans to launch an initial public offering. MongoDB, which develops open-source database software including its namesake #MongoDB #NoSQL database, submitted its IPO plans on Thursday, confirming reports that emerged in August that it was planning to do so. Those reports came after the Wall Street Journal reported in May that the company had hired the Goldman Sachs and Morgan Stanley to act as underwriters. MongoDB’s business model is based around selling sophisticated tools for the open-source software it develops. The idea is that companies begin using its basic software for free, then agree to pay a subscription for all of the paid add-ons MongoDB provides to ensure a better experience using that software. It’s a similar model to Hadoop big-data software provider Cloudera Inc., which also went public earlier this year. The problem for MongoDB is that it’s still losing big money on that model. In its filing, the company provided detailed financial information for the first time, reporting that it lost $45.8 million loss on revenue of $68 million in the six-month period that ended in July. However, that loss was only a fraction of a million dollars more than the same period a year ago, when its revenue was just $45.1 million, demonstrating that the company’s losses relative to revenue are narrowing. Whether the company can ever achieve a profit remains up in the air, however. Holger Mueller, principal analyst and vice president of Constellation Research Inc., said MongoDB has made all of the right moves so far, shifting from an open-source services model to more of a cloud-based, next-generation database player. But he questioned whether the company would be able to sustain the growth its shown over the last year. “The IPO filing shows that management is confident in its ability to deliver growth for the foreseeable future,” Mueller said, who hasn’t heard of any short-term issues with MongoDB’s growth ambitions. “Then again, things are never easy and steady-state in enterprise software.” The difficulty of making a profit in such a competitive market probably explains MongoDB’s decision to go public in the first place. After all, the company will need further capital to keep growing in hopes of turning a profit on the higher revenues at some point. To that end, MongoDB has indicated it’s looking to raise as much as $100 million from the IPO, though that figure could be a placeholder. Well-timed MongoDB’s move also appears to be well-timed, as 2017 has proven to be a livelier one for IPOs in general, coming after a much-publicized IPO drought the previous year. “When you compare the tech IPO market over the last few years, 2017 has been a strong one for startups, and it is indicative of a larger shift in the industry, particularly with regards to cloud technology,” said Ramin Sayer, chief executive officer of Sumo Logic, a provider of log management and analytics services that partners with MongoDB. “Now more than ever, the shift to the cloud and industrywide adoption of other emerging technologies has created an opening for companies like MongoDB to move beyond legacy companies and databases and capitalize on the complex and evolving requirements of business applications.” Indeed, related open-source companies are looking at MongoDB’s IPO hopefully. “MongoDB’s IPO further validates the story, not only around open source technologies and their adoption by the enterprise but the vibrant commercial success of open source-focused businesses,” said Joe McCann, CEO of NodeSource, which makes a software development toolkit for the node.js programming language. Still, despite Ramin’s optimistic view, MongoDB is taking a bit of a gamble as the results of POs this year have been fairly hit and miss, with companies such as Snap Inc. and Blue Apron struggling while the likes of Cloudera and MuleSoft Inc. have managed to stay above their IPO price. It remains to be seen if investors will be willing to make a bet on MongoDB. In addition to the concerns over its profitability, #MongoDB also faces incredibly stiff competition in what is a very crowded database service market. Rivals that offer their own #NoSQL database alternatives include public cloud giants such as #AmazonWeb #Services Inc. and #MicrosoftAzure, and then there’s #Oracle Corp. with its legacy database offering, which MongoDB itself said is its biggest target. “We believe Oracle is incredibly vulnerable because they’ve lost the developer’s heart and soul,” MongoDB Chief Executive Officer Dev Ittycheria said earlier this year. The company was valued at $1.6 billion as of January 2015, according to data from PitchBook. Venture investors included Flybridge Capital, Sequoia Capital and Union Square Ventures.

https://siliconangle.com/blog/2017/09/21/despite-big-losses-database-firm-mongodb-files-ipo/

Global Big Data Services Market 2017 - Teradata, Alteryx, Chartio, Continuum Analytics, Hortonworks, Microsoft

The report studies #BigData Services in Global market Professional Survey 2017 : Size, Share, Trends, Industry Growth, Opportunity, Application, Production, Segmentation, Cost Structure, Company Profile, Product Picture and Specifications during the Forecast period by 2022 The report firstly introduced the Big Data Services basics: definitions, classifications, applications and industry chain overview; industry policies and plans; product specifications; manufacturing processes; cost structures and so on. Then it analyzed the world's main region market conditions, including the product price, profit, capacity, production, capacity utilization, supply, demand and industry growth rate etc. In the end, the report introduced new project SWOT analysis, investment feasibility analysis, and investment return analysis.

Annual estimates and forecasts are provided for the period 2017 through 2022. Also, a six-year historic analysis is provided for Automated Liquid Handling markets. Market data and analytics are derived from primary and secondary research. Company profiles are primarily based on public domain information.

Scope of the report:
Covered in this report
The report covers the present scenario and the growth prospects of the global Big Data Services market for 2017-2021. To calculate the market size, the report considers the new installations.

Top Manufacturers
#Accenture
#Deloitte
#Hewlett-Packard
#IBM
#PricewaterhouseCoopers
#SAP
#Teradata
#Alteryx
#Atos
#Attivio
#Chartio
#Cirro
#ClearStory Data
#Cloudera
#ContinuumAnalytics
#Datameer
#DataStax
#Doopex
#Dell
#Enthought
#Hortonworks
#MAANA
#MapR Technologies
#MarkLogic
#Microsoft
#MongoDB
#MuSigma
#Predixion Software
#SASInstitute

Fior Markets report, Global Big Data Services Market 2017-2022, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers the market landscape and its growth prospects over the coming years. The report also includes a discussion of the key vendors operating in this market. 

The market is divided into the following segments based on geography:
United States
EU
Japan
China
India
Southeast Asia

http://www.openpr.com/news/626424/Global-Big-Data-Services-Market-2017-Teradata-Alteryx-Chartio-Continuum-Analytics-Hortonworks-Microsoft.html

Datos IO Teams with NetApp to Deliver Transformational All-Flash Storage and Cloud Data Protection Solution for Next-Generation Data Center Applications

CHICAGO--(BUSINESS WIRE)-- #MongoDB World ‘17—  #DatosIO, the application-centric cloud data management company, today announced the availability of its new cloud data protection solution that extends the #NetApp Data Fabric by providing next-generation backup and recovery for next-generation databases and cloud applications. Enterprises can now leverage the performance, reliability, and flexibility of NetApp ONTAP software and the agility and web-scale benefits of NetApp #SolidFire array technology with the data protection capability of Datos IO RecoverX software. With this solution, which Datos IO is demonstrating with NetApp at MongoDB World ’17 this week at booth #20, customers can scale business-critical applications on MongoDB and be confident in the recoverability of data at scale and maintain high application uptime.

http://www.businesswire.com/news/home/20170620005527/en/Datos-IO-Teams-NetApp-Deliver-Transformational-All-Flash

Hadoop Servers Expose Over 5 Petabytes of Data

Improperly configured #HDFS -based servers, mostly #Hadoop installs, are exposing over five petabytes of information, according to John Matherly, founder of Shodan, a search engine for discovering Internet-connected devices. The expert says he discovered 4,487 instances of HDFS-based servers available via public IP addresses and without authentication, which in total exposed over 5,120 TB of data. According to Matherly, 47,820 #MongoDB servers exposed only 25 TB of data. To put things in perspective, HDFS servers leak 200 times more data compared to MongoDB servers, which are ten times more prevalent. A report from Binary Edge from 2015 revealed that at the time, Redis, MongoDB, Memcached, and ElasticSearch servers put together exposed a tota of only 1.1 PB of data.

https://www.bleepingcomputer.com/news/security/hadoop-servers-expose-over-5-petabytes-of-data/

MongoDB, ElasticSearch hackers now target Hadoop with ransomware

Following recent cyber attacks on #MongoDB and #ElasticSearch, hackers are now targeting Internet-facing #Hadoop Distributed File System (HDFS) installations. As with the attacks on MongoDB and ElasticSearch, hackers are holding databases for ransom and, in many reported cases, simply deleting the data. It has now been confirmed by Fidelis Cybersecurity Threat Research that these sort of attacks are happening on HDFS instances, with the company estimating that the potential exposure of this attack is around 8,000-10,000 HDFS installations worldwide. In one incident, Fidelis observed an attacker erasing most of the directories and creating a single directory called “NODATA4U_SECUREYOURSHIT”. There was no attempt to claim a ransom or any other communication — the data was simply deleted and the directory name was left as a calling card. Further investigation saw a core issue similar to MongoDB, namely the default configuration can allow “access without authentication.”
http://www.cbronline.com/news/cybersecurity/breaches/mongodb-elasticsearch-hackers-now-target-hadoop-ransomware/

Blockchains for Big Data

#Bigdata arose in the early and mid 2000s to meet internet-scale computation needs: #ZooKeeper at #Yahoo, #BigTable and #MapReduce at #Google, #Cassandra at #Facebook; and so on. Then came open source projects like #Hadoop File System ( #HDFS ), Hadoop MapReduce, Cassandra, and more. By the late 2000s and early 2010s, startups like #MongoDB, #Cloudera, and #DataStax had created businesses to transform the open source successes into enterprise-grade offerings. Now, big data technology is quietly transforming every enterprise backend on the planet. For example, in many places “data warehouses” of relational databases are getting replaced by “data lakes” running big data software. More than $100B annually is going towards big iron compute clusters, the software on top, and the services to keep it all running smoothly. Big Data Challenges But big data has its challenges, which include control, data authenticity and monetization. First, who controls the infrastructure when there are multiple actors involved? For example: If you’re a multinational enterprise, how do you share data around the planet? If you have multiple copies, how do you know which one is the most up-to-date? How do you reconcile a different system administrator role at each regional office? If you’re an industry consortium, how to share control of the ecosystem infrastructure among the companies in your consortium? This is especially hard if those companies are competitors! Why can’t there be data just “out there” as a single shared source of truth that no one on the planet owns or controls, per se? Rather, data would be a public utility like electricity or the internet itself. Second, how well can you trust the data? For example: If you generate the data yourself, how do you prove you were the originator? If you get data from others, how do you know it was truly them? What about crashes and malicious behavior? Machines crash, glitches happen, bits flip. Zombie IoT toasters might be inputting garbage. So after all your fancy Spark calculations, is it still just garbage out? Finally, how do you monetize the data? For example: How do you transfer the rights of the data, or buy rights from others? There’s a long standing dream of a universal data marketplace; how? A New Tool For Big Data: Blockchain Technology The recent surge in blockchain technology was sparked by Bitcoin. Technically, all blockchains are simply databases, but databases with “blue ocean” benefits: decentralized / shared control, immutability / audit trails, and native assets / exchanges. By modern database standards, traditional blockchains have terrible scalability and don’t even have query languages; nonetheless, the blue ocean benefits were enough to capture the imagination of the globe. Better yet, more recent technology — the BigchainDB blockchain database— combines the benefits of distributed databases (scale, queryability) and blockchains (decentralized, immutable / audit trails, assets / exchanges). This new blockchain database technology has the scalability needed in big data environments, by building on top of best-in-class distributed databases like MongoDB. This unlocks the potential for highly interesting applications in big data: shared control of infrastructure, audit trails on data, and the possibility for a universal data exchange. Let’s explore both in detail. Shared Control of Big Data Infrastructure Summary. Being a blockchain database means that control of the database infrastructure is shared across the entities, whether within-enterprise, within a consortium, or across the planet. How. A big data blockchain database like BigchainDB is decentralized, which means that its control can be shared

http://bravenewcoin.com/news/blockchains-for-big-data/

MongoDB 3.4 fills some enterprise database gaps

A few months back, we asked the question as to what #MongoDB wanted to be when it grows up. The answers to that question impact quite a lot of organizations given the popularity of the database now ranked fifth by db-Engines. With current 3.x generation, the company that made its mark with developers as a simple, quick to implement database has been building in more enterprise-grade robustness. With the new 3.4 release, announced this week, Mongo is beefing up its capabilities for managing data placement, database consistency, and extensibility. #Hadoop

http://www.zdnet.com/article/mongodb-3-4-fills-some-enterprise-database-gaps/

MongoDB Delivers Connector for Apache Spark

#MongoDB this week announced a new connector for #Apache #Spark and got it certified by #Databricks, the company behind @ApacheSpark. This week at its MongoDB World conference in New York, MongoDB announced the MongoDB Connector for Apache Spark, which enables developers and data scientists to get real-time analytics from fast-moving data. The product is now available for users to run analytics and glean insights from live, operational and streaming data. MongoDB worked closely with Databricks, the company founded by the team that created Apache Spark. And the MongoDB Connector has received Databricks Certified Application status for Spark. The certification means Databricks has ensured that the connector provides integration and API compatibility between Spark processes and MongoDB. The new Spark connector follows the pattern of MongoDB's existing connector for Hadoop.

http://mobile.eweek.com/database/mongodb-delivers-connector-for-apache-spark.html