The ability to manage and use big data is crucial for nearly every organization, no matter how large or small. Selecting the best data warehouse tool is the first step toward becoming a data-driven organization. According to McKinsey & Company, a company that puts a strong emphasis on customer analytics is 23 times more likely to beat the competition when it comes to customer acquisition. Because big data is constantly expanding and changing, this makes the goal of staying “data-driven” more challenging than ever before.
Some companies are already adopting a cloud-based warehouse to meet the challenge of streamlining and simplifying their data workflow. Moving data from an onsite location to the cloud can improve availability, scalability and security. It can also lower IT costs. Selecting the right data warehouse is sometimes complicated. Each one has pros and cons, and what is the best option for one organization might not work well for another. The following is everything you need to know about the top 5 data warehouse tools.
What is Amazon Redshift? – Amazon Redshift is a fully managed cloud data solution that provides advanced scalability and fast performance with a virtually unlimited amount of concurrent queries. It has the ability to do operations with a columnar approach. The ability to query huge amounts of data quickly without much optimization makes it extremely easy to use. Customers can begin with a couple hundred gigabytes and scale to include a petabyte or even more.
Redshift has the ability to integrate well with systems such as DynamoDB and S3. With PostgreSQL wire protocol, it has the ability to integrate with virtually any tool a user may need. Redshift is a column oriented tool. Columnar storage works by utilizing high performance disks and parallel processing. Each data warehouse has a collection of nodes that are in clusters. Each cluster runs its own engine and has one or more databases. A top feature includes Redshift Spectrum. This enables users to run queries against data that is not structured and directly from Amazon S3. This eliminates the need for loading and then transformation.
What are the Pros and Cons? – A few of the top selling points for Amazon Redshift is that it is extremely fast and provides exceptional performance. It’s easy to set up and get started and offers a variety of pricing options. Redshift provides great overall security, with SSL encryption that will protect data in transit. One of the disadvantages includes the inability to quickly load from alternate sources. Redshift does not provide optimal performance for live web applications.
What is the Pricing? – Redshift offers flexible pricing with options that include pay-as-you-go and the ability to pay separately for storage and compute. There is an additional cost for Redshift Spectrum. Customers will pay for the amount of canned bytes during SQL queries. Concurrency Scaling has more query processing as needed, with customers only charged for what they use. Another option is using Reserved Instance. Customers commit to 1 or 3 year terms that can save them up to 75 percent off on-demand prices. There is also a free trial that new customers can use for two months. The pay-as-you-go model has no upfront costs and comes with four cluster types to choose from:
- dc2.large (2 vCPU, 15 GiB memory, 0.16 TB storage) – $0.25/hour
- ds2.xlarge (4 vCPU, 31 GiB memory, 2 TB storage) – $0.85/hour
- dc2.xlarge (32 vCPU, 244 GiB memory, 2.56 TB storage) – $4.80/hour
- ds2.8xlarge (36 vCPU, 244 GiB memory, 16 TB storage) – $6.80/hour
2.Azure SQL Data Warehouse
What is Azure SQL Data Warehouse? – This particular cloud data warehouse is from Microsoft. Azure SQL is a fully managed cloud-based warehouse that has the ability to effectively query extremely large datasets. Using SQL analytic functions, it has the ability to transform data from a variety of sources into a single database. This is a cloud platform that offers the ability to build applications quickly, featuring limitless analytics.
Users can query data using either scaled provisioned resources or serverless on demand. They offer the ability to ingest and manage data for machine learning needs as well as immediate BI. Azure also offers the Azure Data Catalog. The catalog provides users with a better understanding of their data sources. The catalog has a crowdsourcing model of various annotations and metadata. It simplifies the process of finding data assets.
What are the Pros and Cons? – Azure SQL is an extremely fast and scalable data warehouse tool that is able to meet the demands of a large organization. It’s a good choice for artificial intelligence applications. It offers facial and voice recognition APIs and automated language translation. This particular data tool has perhaps too many options that are often confusing for customers. There is a steep learning curve involved. There have also been complaints that it has a slow user interface. One of the biggest drawbacks, however, is that customers often complain about the complicated pricing system. Reviewers have stated that it’s difficult to estimate costs, especially in the beginning.
What is the Pricing? – Azure SQL pricing is more complicated than most of the other data warehouse tools. Their system uses compute charges as well as storages. It uses the Microsoft metric called Data Warehouse Unit (DWU). Using 100 DWUs in the Eastern region of the United States is $1,125 per month.
- The cost for 1,000 DWUs is $11,125 per month using their linear pricing scale. Prices for storage in the same region are $135 each month for a single terabyte.
- It is $13,517 each month for a 100 terabytes. It’s important to note that customers don’t pay for storage transactions or inbound data transfers. They pay for data storage at rest and outbound data transfers.
What is Google BigQuery? – Google BigQuery is Google Cloud Platform’s data warehousing solution in the cloud. To enable lightning-fast SQL queries, BigQuery uses the power of Google’s Dremel tool for interactively searching through massive datasets. With BigQuery, users are no longer obligated to install or manage the IT infrastructure. If a particular business relies on real-time data analytics, this particular data tool is likely a good choice. It also includes several types of ETL data pipelines from Google as well as non-Google sources.
In April 2019, Google brought out a new service for BigQuery. The analytics warehouse is now available in Sheets, which is a web-based tool for spreadsheets. The sheets are no longer subject to the limitations of the basic Google spreadsheets. Specifically, there are no longer row limits. A user can take data with billions of rows and make it into a pivot table.
What are the Pros and Cons? – Reviews on sites such as G2 are generally positive. One of the best features of Google BigQuery is its scalability. Like the other large competitors, Amazon and Microsoft, it also excels at managing and crunching large amounts of data efficiently. It’s also fast and easy to use. It’s fully managed, which means monitoring and maintenance responsibilities are minimal. BigQuery, however, is likely overkill for smaller organizations that don’t have such demanding analytic workflows. Another drawback includes difficulty executing some SQL queries with BigQuery.
What is the Pricing? – This particular tool features pay-as-you-go pricing. The first 10 gigabytes of storage along with the first terabyte of query data are free each month. Beyond this limit, Google BigQuery charges $0.02/gigabyte for active storage and $0.01/gigabyte for long-term storage. Google BigQuery offers both on-demand and flat-rate pricing for running SQL queries:
- On-demand – $5/terabyte of query data
- Flat-rate – $10,000/month for 500 BigQuery slots (or $8,500/month if paid each year)
What is Panoply? – Panoply is a data platform built for analytics. They combine cloud data infrastructure, AI automation and data integrations to expertly manage and organize data. It has the ability to ingest and integrate data from several sources. It’s important to note that Panoply is an extension of Amazon Redshift. It can make use of Amazon S3 storage and Amazon Elasticsearch Service. Customers can receive training through documentation, webinars, and live online.
Panoply will work well for engineers, architects, scientists and data analysts that need disparate data that is quickly available and usable. Panoply is best suited for organizations without a deep familiarity with data warehouses and the cloud. By automating the ELT process, Panoply makes it easy to get a cloud data warehouse up and running in minutes. Many users also praise Panoply’s customer support team for their helpfulness and responsiveness.
What are the Pros and Cons? – One of the benefits of Panoply is that a user can usually get started within minutes without any technical knowledge. It’s easy to build connections between different data sources. Customers are happy with the great customer service and several flexible pricing options. One of the cons is the lack of visualization tools. A user will need external software to visually view all the data. Panoply is not quite as high-powered as some of the other cloud data warehouse alternatives. As a newer cloud data warehouse tool, Panoply can be subject to performance issues.
Of 15 reviews, Capterra gives Panoply a 4.1 out of 5 rating. A Gartner reviewer and project development manager calls Panoply “а turnkеy busіnеss іntеllіgеnсе sоlutіоn fоr аny smаll busіnеss tо сrеаtе dаshbоаrds аnd mаkе dаtа drіvеn dесіsіоns аt а frасtіоn оf thе оff-thе-shеlf sоlutіоns соst. Nо dаtа еngіnееr, nо dаtа аnаlyst, nо busіnеss аnаlyst rеquіrеd.”
What is the Pricing? – Customers can try Panoply for 14 days with a free trial. There are four options to choose from if users decide to purchase Panoply.
- Starter – The most basic option starts at $325 per month.
- Pro – This includes live chat support, automated backups and user permissions for $665 per month.
- Business – For $995 each month, customers will receive guaranteed support within 1 hour, screen share support and platform analytics.
- Enterprise – This is a customized pricing option. This will include advanced security and is available in 19 global regions.
What is Snowflake? – This is software as a service (SaaS) solution. There isn’t any hardware or software to install or manage. Everything completely runs in the cloud. This means that it isn’t software that a user can install. Snowflake takes care of all the management and maintenance. The architecture consists of three basic layers. These include database storage, query processing and cloud services.
Snowflake markets itself as faster, more flexible and easier to use than traditional warehouse data tools. They aren’t built on a big data platform, but uses an SQL engine with unique cloud features. There is the option of hosting Snowflake on either Microsoft Azure or Amazon Web Services. It provides insights into aspects of each program and into users’ behavior. Snowflake has the ability to work well with datasets that are both structured and unstructured.
What are the Pros and Cons? – Snowflake is both quick and agile. It features multi-cluster shared data structure that provides extraordinary performance. Snowflake can access data that is already deleted or changed. This ability to access historical data is a definite plus. Secure data sharing is another positive feature. This enables users to more easily share tables and databases. Snowflake also works well with AWS S3. Drawbacks are primarily technical. In particular, are difficulties with suboptimal query times and specific integrations. Finally, there are complaints regarding slow or difficult customer service experiences. TrustRadius gives Snowflake a score of 9 out of 10.
What is the Pricing? – Snowflake stakes a claim to the “most affordable data warehouse in the world.” Using an on-demand pricing system, customers pay $23 each month per terabyte for storage in Snowflake. It’s $40 each month for on-demand per terabyte.
- Standard – $2.00/credit
- Premier – $2.25/credit
- Enterprise – $3.00/credit
- Business-critical – $4.00/credit
These are five of the best options available when selecting the best data warehouse tool for your organization. Each of these five options has generally received high reviews. It’s necessary to select a data warehouse that fits with your business model as well as your budget. Correctly storing and analyzing data is now crucial to the success of almost any type of business.
Picking the right cloud data warehouse is an essential component of your data analytics workflows, but it’s only one part of the puzzle. Extracting, transforming, and loading information into your cloud data warehouse will be of little use if you aren’t able to intelligently analyze this data and mine it for valuable insights.
ironFocus’ team of data experts will help make your data work for you. From identifying the most promising prospects for hunting down new growth opportunities, ironFocus offers a full suite of services that will take your business to the next level. Want to learn more? Get in touch with us today for a chat about your needs and objectives.