Best Software to Build a Data Warehouse in the Cloud

ScienceSoft has been rendering data warehouse consulting services for more than 15 years.

What is a cloud data warehouse?

A cloud data warehouse is a system, which uses the space and compute power allocated by a cloud provider to integrate and store data from disparate data sources. It is employed for data structured storage, analysis and reporting.

Cloud vs. On-premises DWH

Aspect
Cloud data warehouses
On-premises data warehouses
Scalability
Availability
Security
Performance
Cost-effectiveness

Cloud DWH key features

General features

  • Flexible querying with SQL (including big data).
  • Data ingestion with ETL/ELT.
  • Quick deployment.
  • Automation of DWH maintenance tasks (backups, patching, replication, etc.)

Integration

  • Relational data.
  • Structured big data.
  • Unstructured data, including real-time data.
  • Federated query support.
  • Integration with BI and analytics software.

Performance

  • Massively parallel processing.
  • Optimized data storage for high performance query processing (columnar data storage, data compression, etc.).
  • Materialized view support and result-caching.
  • ML capabilities to manage performance and concurrency.

Scalability

  • On-demand near-infinite scaling of compute and storage resources.
  • Possibility to scale compute and storage separately.

Reliability

  • High availability (up to 99,99%).
  • Fault tolerance due to automatic backups, (re)-replication and restore.

Agile pricing

  • Consumption-based and flat-rate pricing options.
  • Controllable pricing with the possibility to save up with long-term commitments.

Security and compliance

  • Data encryption.
  • Built-in authentication and authorization.
  • Columnar-level access control.
  • Automated threat detection, vulnerability assessment, etc.
  • Compliance to national, regional, and industry-specific requirements.

Top 5 Cloud Data Warehouses

The presented cloud data warehouse solutions are recognized leaders of Gartner Magic Quadrant and Forrester Wave reports. All of them are suitable for mid-sized and large businesses.

Amazon Redshift
Description

An enterprise-level DWH to handle diverse workloads by scaling up and down storage and compute and paying for them separately.

  • Agile SQL data querying (including big data)
  • Native integrations with the AWS ecosystem (including Amazon S3)
  • Federated queries support
  • Advanced security, etc.
Best for:

Companies that have already invested in the AWS ecosystem and those seeking high DWH performance with huge data sets.

Pricing
  • On-demand pricing starts from $0.25/hour (depends on the type and number of nodes in the cluster).
  • Reserved instance pricing includes three options (No, Partial, All Upfront) and allows saving up to 75% over the on-demand option.
Azure Synapse Analytics
Description

The Microsoft product to unify enterprise data warehousing and big data analysis.

  • Quick DWH deployment and SQL data querying
  • Native integrations with a data lake, operational databases, BI and ML software
  • Intelligent workload management
  • Comprehensive security features
  • Separate billing for compute and storage, etc.
Best for:

Companies looking for a unified workspace to deliver end-to-end analytics with integrated BI, ML and AI capabilities.

Pricing
  • Data storage $122.88 per TB/month ($ 0.17/TB/hour). The data storage size includes your DWH data and 7 days of incremental snapshot storage.
  • Storage transactions are not billed.
  • Query performance pricing depends on the service level and region.
Google BigQuery
Description

A cloud-based DWH that allows SQL querying against huge data sets with results delivered in seconds.

  • Multi-cloud capabilities
  • NLP
  • Built-in integrations with a data lake, operational databases, big data ecosystem, BI and AI, etc.
Best for:

Data mining and varied workloads.

Pricing

Storage costs $0.02 per GB/month ($0.01 per GB/month for long-term storage).

Streaming inserts $0.01 per 200 MB.

For query performance, 2 subscription options are available:

  • Pay-as-you-go ($5 per TB, 1st TB/month is free).
  • Flat-rate pricing (from $10,000/ month for a dedicated reservation of 500 processing units).

Loading, copying or exporting data, metadata operations, deleting datasets, tables, views, etc. – free.

Oracle Autonomous Data Warehouse
Description

An easy-to-run cloud DWH service with automatic scaling and management of patches and updates.

  • Elastic separate scaling of storage and compute
  • SQL Developer and BI tools support
  • Built-in support for analytical SQL and ML
  • Profound security
  • Deployment variations, etc.
Best for:

Companies that want to eliminate traditional database administration tasks and save during peak performance time with autoscaling.

Pricing
  • Compute costs $1.3441/CPU/hour
  • Data storage – $118.40 per TB/month (in the public cloud).
IBM Db2 Warehouse on Cloud
Description

An elastic cloud DWH built for high-performance analytics and ML workloads.

  • Flexible SQL data querying
  • Integration with Apache Spark
  • Compatibility with IBM Netezza and IBM workloads
  • Built-in ML and geospatial capabilities
  • Independent scaling of storage and compute
  • Deployment on multiple cloud providers (IBM Cloud, AWS), etc.
Best for:

Hybrid cloud deployment needs and intensive analytics workloads.

Pricing
  • Flex One:

    Data storage $0.005 per 10GB/hour

    Compute $0.68 per Instance/hour, $0.05 per Virtual Processor Core/hour.

  • Flex:

    Data storage - $0.48 per 1TB/hour

    Compute $2.11 per Instance/hour, $1.48 per 16 Virtual Processor Cores/hour.

  • Flex performance:

    Data storage$2.03 per 2400GB/hour

    Compute $7.76 per Instance/hour, $2.60 per 24 Virtual Processor Cores/hour.

These platforms offer similar functionality within the key criteria for choosing DWH technology – scalability, reliability, flexibility, and security. Thus, the decision on what cloud DWH platform to opt for mostly depends on:

  1. A platform’s performance (ability to accomplish the assigned tasks).
  2. Implementation costs, which can be different for every particular situation.

Implementation of a cloud data warehouse

Having 15+ years of hands-on experience in delivering DWH solutions, ScienceSoft can provide you with a flexible centralized storage on a fitting cloud platform and enable analytics capabilities to optimize internal business processes and enhance the decision-making.

Cloud DWH Consulting

  • Analyzing your business needs and eliciting requirements for a future DWH solution.
  • Designing a cloud DWH implementation/migration strategy.
  • Outlining the optimal cloud DWH platform and its configurations.
  • Consulting on data integration and data quality procedures.
  • Conducting admin training.

If required, we supplement our consulting services with tech expertise and implement the DWH solution in accordance with the worked-out strategy.

Cloud Data Warehouse as a Service (DWaaS)

For you to avoid the efforts on cloud DWH development, implementation and management, we customize a cloud-based data warehouse and rent it out to you on a subscription fee basis.

About ScienceSoft

ScienceSoft is a global IT consulting and IT service company headquartered in McKinney, TX, US. Since 2005, we assist our clients in delivering DWH solutions with the help of end-to-end data warehousing services to encourage agile and data-driven decision-making. Our long-standing partnerships with global technology vendors such as Microsoft, AWS, Oracle, etc. allow us to bring tailored end-to-end cloud data warehousing solutions to business users.