Data Warehouse Software: 5 Best Data Warehousing Tools

ScienceSoft has been helping businesses choose optimal data warehousing solutions for 15 years.

Data warehouse systems: the essence

Data warehouse software is a central component of a company’s or a department’s data ecosystem that serves to retrieve, aggregate, and store data from internal and external data source systems for further analysis and reporting.

Data warehouse system: key features

Deployment options

  • On-premises deployment.
  • Cloud deployment (public, private, multi-cloud).

  • Hybrid deployment.

Data integration

  • Data processing with ETL/ELT.
  • Full and incremental data extraction/load.

  • Structured, semi-structured, unstructured data ingestion.

  • Big data ingestion.

  • Streaming data ingestion.

  • Data loading and querying using SQL.

Data storage

  • Subject-oriented data storage.
  • Time-variant (data from the historical point of view) data storage.

  • Nonvolatile (read-only) data storage.

  • Granular data storage.

  • Metadata storage.

Performance

  • Massively parallel processing.
  • Improved data searching efficiency (materialized view support, data indexes, result-caching, etc.).

  • ML capabilities to manage DWH performance and concurrency.

Security and compliance

  • Data encryption.
  • Securing data access with user authentication and authorization.
  • Fine-grained access control (row- and column-level).
  • Compliance with national, regional, and industry-specific regulations (for example, GDPR, HIPAA, PCI DSS).

Top 5 data warehouse products for comparison

Our list of data warehouse tools suitable for most mid-sized and large businesses features leaders in the Gartner Magic Quadrant and Forrester Wave for Data Management Solutions for Analytics.

Amazon Redshift

Best for: petabyte-scale cloud analytics

FEATURES

  • Automated infrastructure provisioning.
  • SQL data querying (including big data).
  • Native integrations with the AWS ecosystem, including S3, Amazon EMR, AWS Glue, Amazon SageMaker, Amazon QuickSight.
  • Federated query support.
  • Automated backups and cluster health monitoring.
  • Result caching.
  • Separate storage and compute scaling.
  • Data encryption in transit and at rest.
  • Row- and column-level security.

Pricing

  • On-demand pricing: $0.25/hour (dc2.large) - $13.04/hour (ra3.16xlarge).
  • Reserved instance pricing can save up to 75% over the on-demand option (in a 3-year term).
  • Data storage (RA3 node types): $0.024/GB/month.

Azure Synapse Analytics

Best for: end-to-end cloud analytics

FEATURES

  • Unified workspace for building analytics solutions.
  • SQL querying of relational and non-relational data.

  • Multilanguage support (T-SQL, Python, Scala, Spark SQL or .Net).

  • Native integrations with Apache Spark, Power BI, Azure ML, Azure Stream Analytics, Azure Cosmos DB, etc.

  • Automated restore points and backups.

  • Workloads isolation.

  • End-to-end data encryption.

  • Dynamic data masking.

  • Granular access control.

Pricing

  • Compute on-demand pricing: $1.20/hour (DW100c) - $360/hour (DW30000c).
  • Compute reserved instance pricing can save up to 65% over the on-demand option (in a 3-year term).
  • Data storage: $122.88/TB/month.

     

Oracle Autonomous Data Warehouse

Best for: enterprise DWH

FEATURES

  • Deployment in the Oracle public cloud (shared/dedicated infrastructure) or in the customer’s data center.
  • Automated scaling, performance tuning, patching and upgrades, backups and recovery.

  • Querying across structured, semi-structured, unstructured data types.

  • Connection with custom applications and third-party products via SQL*Net, JDBC, ODBC.

  • Native integration with Oracle Analytics Desktop.

  • Connectivity to Oracle Cloud Infrastructure Object Storage, Azure Blob Storage, Amazon S3.

  • Graph and spatial analytics.

  • Independent storage and compute scaling.

  • Data encryption at rest and in transit.

  • Multifactor authentication.

Pricing

  • Compute: $1.3441/CPU/hour.
  • Data storage: $118.40/TB/month (in the public cloud).

     

Teradata Vantage

Best for: enterprise-scale workloads

FEATURES

  • Public cloud (AWS, Azure, Google Cloud), multi-cloud, on-premises (Teradata IntelliFlex, VMware) deployment.
  • All data types (structured, semi-structured, unstructured.)

  • Support for SQL, R, Python.Integration with Amazon S3, Azure Blob Storage, Hadoop, etc.

  • Pre-built processing engines (Advanced SQL Engine, ML Engine, Graph Engine).

  • User authentication and authorization.

Pricing

Consumption-based pricing:

  • Advanced SQL engine – $5/vantage unit (Amazon EC2 instance/Azure VM).

  • Storage: primary - $0.291/TB (Amazon EBS/Azure Premium), backup - $0.044/TB (Amazon S3) and $0.045/TB (Azure Blob Storage).

SAP BW/4HANA

Best for: on-premises deployment

FEATURES

  • SQL-querying of any data type (structured, semi-structured, unstructured).
  • Integration with SAP and Non-SAP applications and data sources.

  • Simplified data modeling and administration.

  • Classifying data depending on the cost and performance requirements for it.

  • Built-in predictive analytics and text analysis capabilities.

Pricing

Prices are available by direct request to SAP.

Data warehouse implementation

With a 15-year experience in delivering data warehouse solutions, ScienceSoft helps you establish flexible data storage on a fitting platform, populate it with data from your internal and external sources, set up ETL processes, and integrate your DWH into a comprehensive analytics system.

Data warehouse consulting

  • Analyzing your data storage needs and eliciting requirements for a future DWH solution.
  • Designing a DWH implementation/migration strategy.
  • Outlining the optimal set of tools and the technology stack making up a DWH.
  • Advising on data integration and data quality procedures.
  • Conducting DWH admin training.

Data warehouse implementation

  • Data storage needs analysis and DWH solution architecture design.
  • Data modeling.
  • ETL/ELT setup.
  • DWH platform integration into the existing data environment (a data lake, big data platform, BI tools, etc.).
  • Setting up data- and metadata management procedures
  • Data cleaning and data migration.
  • Admin & user training.
  • DWH support and evolution (if required).

About ScienceSoft

ScienceSoft is a global IT consulting and IT service provider headquartered in McKinney, TX, US. Since 2005, we offer a full range of data warehousing services to help companies select suitable DWH technologies, integrate them into the existing data environment, and support analytics workflows.