Data warehousing improves access to information, speeds up query-response times, and allows businesses to fetch deeper insights from big data. Previously, companies had to invest a lot in infrastructure to build a data warehouse. The advent of cloud technology has significantly reduced the cost of data warehousing for businesses.
Today, there are cloud-based data warehousing tools that are fast, highly scalable, and available on a pay-per-use basis. Here is our pick of some of the best data warehouse tools out there and what they have to offer:
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1. Amazon Redshift
Redshift is a cloud-based data warehousing tool for enterprises. The fully-managed platform can process petabytes of data in seconds. That's why it's suitable for high-speed data analytics. It also supports automatic concurrency scaling. The automation increases or decreases query processing resources to match workload demand. This way, you can execute hundreds of concurrent queries without the operational overhead. Additionally, Redshift allows you to scale your cluster or switch between node types. Thus, it enables you to optimize data warehouse performance and cut operational costs.
Amazon Redshift Pricing
Amazon Redshift has different pricing structures. On-demand pricing is billed per hour. It starts at $0.25 per hour. However, the total cost depends on the number of nodes in a cluster. You can use Redshift's pause and resume feature to save money in this tier.
Managed store pricing for Amazon Redshift starts at $0.024 per GB of data, per month. The price varies between regions. This price does not include the cost of storing backups.
Related Reading: How to Set Up an Amazon Redshift Data Warehouse
2. Microsoft Azure
Azure SQL data warehouse is a cloud-based relational database from Microsoft. You can optimize it for petabyte-scale data loading/processing and real-time reporting. The platform has a node-based system, and it employs massively parallel processing (MPP). The architecture is suitable for optimizing queries for concurrent processing. Thus, it enables you to extract and visualize business insights much faster.
The data warehouse is compatible with hundreds of MS Azure resources. For example, you may build intelligent apps with the platform's machine learning tools. Also, the platform lets you store different types of structured and unstructured data. The data may come from diverse sources, such as on-premise SQL databases and IoT devices.
Microsoft Azure SQL Pricing
Price for serverless compute on Azure SQL database starts at $0.52 per V-core/hour. Here, V-core is one hyper-thread. Serverless compute in Azure runs on Gen 5 logical CPUs. Storage cost in Azure is $0.115 per GB/hour, with a minimum of 5GB storage and a maximum of 4TB. Additional charges for backup storage are $0.20 per GB/month.
3. Google BigQuery
BigQuery is a cost-effective data warehousing tool with built-in machine learning capabilities. You can integrate it with Cloud ML and TensorFlow to create powerful AI models. It can also execute queries on petabytes of data in seconds for real-time analytics.
This cloud-native data warehouse supports geospatial analytics. With it, you may analyze location-based data or discover new lines of business.
BigQuery can separate compute and storage. So, it enables you to scale processing and memory resources based on business needs. Separation lets you manage the availability, scalability, and cost of each resource.
Google BigQuery Pricing
There is separate pricing for storage and queries in BigQuery. Storage is differentiated as active or long-term. The latter is data stored in partitions that have not been modified in more than 90 days. The cost for active Google BigQuery storage is $0.020 per GB/month. The same or long-term storage is $0.010 per GB/month. The first 10 GB/month is free for both types of data.
Querying in Google BigQuery has two pricing models - on-demand, and flat-rate. On-demand pricing for Google BigQuery is $5 per TB, with 1 TB free, every month. Monthly flat-rate pricing is billed at $10,000 per 500 slots. An annual contract, on the other hand, is billed at $8,500 per 500 slots/month. BigQuery's flat-rate pricing is ideal for businesses that deal with large volumes of data and want predictable data costs.
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You may use Snowflake to set up an enterprise-grade cloud data warehouse. With the tool, you can analyze data from various unstructured and structured sources. The multi-cluster, shared architecture separates storage from processing power. Thus, it allows you to scale CPU resources based on user activities. The scalability also accelerates querying performance to deliver actionable insights faster.
Snowflake's multi-tenant design lets you share data across your organization in real-time. You can do this without moving any data.
Compared to most other data warehousing tools that bill you based on the amount of data processed, Snowflake's pricing is based on per-second billing. Compute cost for Snowflake is billed per second, with a minimum of 60 seconds. However, the price varies according to the region, the platform, and the selected pricing tier. Users can opt between Standard, Enterprise, Business Critical, and VPS. The average compute costs for the Standard tier is $0.00056 per second, per credit. The same in the Enterprise tier is $0.0011 per second, per credit.
5. Micro Focus Vertica
Vertica is an SQL data warehouse available in the cloud on platforms like AWS and Azure. You may also deploy it on-premise or as a hybrid. The tool supports columnar storage and uses MPP to increase query speed. Its shared-nothing architecture reduces competition for shared resources.
Vertica offers built-in capabilities for analytics. These include machine learning, pattern matching, and time series. It also supports standard programming interfaces, such as OLEDB. The software uses compression to optimize storage.
Micro Focus Vertica Pricing
Vertica has a free community tier for up to 1 TB and three nodes. The paid cloud tier bills customers on a per-hour basis. The cost of computing on Vertica depends on the region and the fulfillment option, such as a 64-bit Amazon Machine Image. Pricing starts at $2 per hour.
Teradata is a data warehousing platform for collecting and analyzing vast amounts of enterprise data in the cloud. The tool provides super-fast parallel querying infrastructure. This way, it speeds up access to actionable insights. Teradata's QueryGrid delivers best-fit engineering. It does this by deploying multiple analytic engines to deliver the right tool for the job.
It also employs smart in-memory processing to optimize database performance at no extra costs. Using SQL, the data warehouse connects to commercial and open-source analytical tools.
Teradata works on a pay-as-you-go model. However, the company does not disclose its pricing.
7. Amazon DynamoDB
DynamoDB is a scalable NoSQL, cloud-based database system for enterprises. It can scale querying capacity to 10 or even 20 trillion requests per day over petabytes of data. Also, it uses key-value and document data management to create a flexible schema. Thus, tables can scale automatically by adding new columns based on growing requirements.
The database system comes with DynamoDB Accelerator (DAX). That's an in-memory cache that can shorten the time required to read tabulated data from milliseconds to microseconds. Thus, it powers super-fast querying processes, including at millions of request per second.
Amazon DynamoDB Pricing
DynamoDB has a free tier that offers 25 GB of data storage and 2.5 million stream read requests. For storage and computing that exceeds the free tier, users can choose between on-demand pricing and provisioned-capacity pricing.
On-demand pricing for Amazon DynamoDB is billed at $0.25 per million reads and $1.25 per million writes. Storage cost is $0.25 per GB of data.
Provisioned-capacity pricing is suitable for users that deal with fluctuating traffic. It allows them to scale the demand up or down automatically, thus saving them compute costs. This model applies flexible pricing per hour depending on the provisioned reads and writes. The compute cost of Amazon DynamoDB increases as the demand goes up, and likewise. Data storage cost is fixed at $0.25 per GB.
PostgreSQL is an open-source database management solution available in the cloud. SMEs and large enterprises alike can use the resource as their primary database. For example, you may use it to drive internet-scale business applications. To work with geospatial data, consider integrating PostgreSQL with the PostGIS extension. The integration will enable you to offer location-based business solutions.
The platform supports both SQL and JSON querying. And you can optimize database performance with features like Multi-Version Concurrency Control (MVCC).
It is open-source software, which is available free of cost.
9. Amazon Relational Database Service (RDS)
Amazon RDS enables you to create a cost-effective cloud-based relational database. The platform is compatible with six database engines, including PostgreSQL and Amazon Aurora. You can generate replication within the system to boost availability for operational workflows. For instance, Read Replicas let you divert read traffic from your primary database to virtual copies. They're an option when you need to serve high-volume applications. You may also scale your RDS computing and memory capabilities to 32 vCPUs and 244 gigabytes of RAM.
Amazon RDS Pricing
Cost of Amazon RDS is a little more complex, compared to other data warehousing tools listed here. Pricing for Amazon RDS depends on:
- The preferred database engine
- Single or multiple deployments
- On-demand or reserved instances, billed hourly
As an example, the compute cost for Amazon RDS for PostgreSQL is $4.27 per hour for one instance in the on-demand pricing tier. The same in the reserved-instance tier is $2.73 per hour, for a one-year contract. Storage cost is uniform across database engines at $0.115 per GB/instance.
10. Amazon Simple Storage Service S3
Amazon S3 can serve cloud storage needs at scale for small and large enterprises. The scalable, object-oriented service also supports big data analytics. It stores data in "buckets," each of which can hold up to 5 terabytes. The platform offers several cost-effective storage class options. For example, you may lower costs using S3 Standard-IA to store occasionally-accessed data.
Amazon S3 Pricing
Storage costs for Amazon S3 vary according to the storage class. Users can choose from 7 storage classes, starting with Standard. Storage is billed per GB/month. For example, in Standard class, the first 50 TB will cost you $0.023 per GB/month. The cost drops fractionally as the amount of data goes up.
Compute costs on Amazon S3 vary according to the type of requests, the amount of request, and the storage class.
11. SAP HANA
SAP HANA is a cloud-based resource with in-memory caching capabilities. Thus, it supports high-speed, real-time transaction processing, and enterprise-wide data analytics. It also provides a simple, centralized interface for data access, integration, and virtualization.
With data federation, you can query remote databases without moving your data. These data sources include Hadoop and SAP Adaptive Server Enterprise (SAP ASE). SAP HANA supports text and predictive analytics and intelligence-driven app development.
SAP HANA Pricing
SAP does not disclose its pricing information for HANA.
MarkLogic provides a NoSQL database system with powerful querying and versatile application services. The schema-agnostic platform lets you ingest data of any form or type, as is. That's because it has native storage for predefined schemas. Supported formats include geospatial data, JSON, RDF, and massive binaries like videos. Its built-in search engine simplifies querying once you've loaded data. It enables you to start asking questions and getting answers right away.
MarkLogic bills according to consumption. It has three pricing tiers:
- Low priority fixed tier: Compute cost under this tier is $0.074 per hour/MCU. Storage is billed at $0.10 per GB/month.
- Standard on-demand: This lets users scale their demand up or down. The cost of MarkLogic under this tier is $0.125 per hour/MCU. Storage is billed at $0.10 per GB/month.
- Standard Reserved: Users that expect a fixed amount of traffic can reserve compute capacity annually. Under this pricing tier, computation is billed at $0.071 per hour/MCU. Storage cost remains the same as the other two tiers.
MariaDB is an enterprise-grade database tool with support for customer-facing applications. You may also use it to create a columnar database to perform real-time analytics. The solution employs massive parallel processing (MPP) too. So, it enables you to execute SQL queries across hundreds of billions of rows. You don't need to create indexes before doing this. MariaDB can scale out based on workload and business needs, or in the cloud.
The price of MariaDB Cloud starts at $0.45 per hour for the Foundation tier. The company does not disclose its pricing mechanism in detail.
14. Db2 Warehouse
IBM Db2 Warehouse is a fully-managed, scalable cloud data storage platform. It's suited to analytics and artificial intelligence applications. The system provides built-in machine learning tools. You may exploit these to train and deploy ML models within the ecosystem. Supported languages for ML developments include SQL and Python.
Also, Db2 Warehouse has an intuitive UI or REST API. You may use the tools to manage the elastic scaling of processing power and storage. Multiple servers crank up the platform's MPP capabilities. These facilitate super-fast concurrent querying for large data sets.
Db2 Warehouse Pricing
Db2 Warehouse offers users 9 pricing tiers. Flex One is the most basic tier, which gives users a single-partitioned instance. It is ideal for companies that are starting off with a data warehouse project. Compute cost under this tier is $0.68 per instance/hour.
The Oracle's "autonomous data warehouse" runs on the Exadata cloud infrastructure. The self-driving platform leverages adaptive machine learning to automate administrative tasks. These range from tuning and patching to monitoring, upgrading, and securing your database.
Creating an autonomous Exadata data warehouse is easy. Start by specifying tables and loading your data with only a few clicks. The system employs parallelism and columnar processing to boost performance and scalability.
Oracle has two pricing structures for its autonomous data warehouse. The pay-as-you-go model is billed at $2.52 per Oracle compute unit (OCPU)/hour. Storage cost for the same is $222 per TB/month.
The monthly flex model lets users reserve compute capacity in advance. It is billed at a price of $1.68 per OCPU/hour. Storage under this tier costs $148 per TB/month.
16. BI360 Data Warehouse
Solver BI360 enables enterprises to consolidate massive amounts of data from disparate sources. These include CRM, ERP, accounting software, and unstructured data stores. It's pre-configured to simplify database deployment and business intelligence workflows. The cloud-based solution has intuitive dashboards and analytics interfaces. For example, you may use the Data Explorer to explore data. It's also possible to add modules and dimensions.
The data warehouse runs on MS SQL Server. And it offers built-in automated data loading tools. These make light work of database querying and searching.
BI360 Data Warehouse Pricing
BI360 does not disclose its data warehouse pricing. However, according to some estimates, the price for BI360 data warehouse is $312 per user/month.
Cloudera's operational database is a low-latency, high-concurrency cloud-hosted platform. It's ideal for analyzing big data and extracting real-time business intelligence. The resource supports portable and flexible distribution, which is cost-effective. Thus, it provides the necessary elasticity to move between on-premises and cloud-based servers.
The platform utilizes HBase to create columnar NoSQL storage for unstructured data. But Kudu helps to create a relational database for structured data within Cloudera. Also, the tool supports predictive modeling based on real-time and historical data.
Cloudera data warehouse is billed hourly. It starts at $0.72 per hour/instance.
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Related Reading: How to Choose the Right Data Warehouse Tool for Your Business
Originally published on August 21st, 2019.