Top Tools / September 21, 2021
StartupStash Team

The world's biggest online directory of resources and tools for startups and the most upvoted product on ProductHunt History.

27 Best Data Warehouse Tools

To understand why data warehouse tools are important, you need to understand what drives businesses to succeed in today's world?

Data.

Big data and data analytics are some of the most prominent on-demand technologies in use today. Data Warehousing and Data Analytics may have sounded like a novel concept in the past, but they are now some of the most significant tools required to cater to various services given by large corporations all over the world. Many businesses today rely on data warehousing tools.

In this top tool list, we have gathered some of the best Data Warehouse Tools out there that can help you make smarter decisions for your business.


1. Green Plum

Green Plum is a massively parallel open-source analytics, AI, and Machine Learning platform. Data Transformation, Text Data, Graph Data, Time-Series Data, and Geospatial Data are all covered by Greenplum's data analytics. Java, Perl, Python, pgSQL, and R are among the programming languages supported.

Key Features:

  • Scale interactive and batch-mode analytics to petabyte-scale datasets while maintaining query performance and throughput.

  • more control over the software you use, less vendor lock-in, and more open input into product direction

  • Reduced data silos by combining analytic and operational tasks, such as streaming ingestion, in a single, scale-out environment.

Cost:

This tool is available for free.


2. Xplenty

Xplenty is a data warehousing platform that integrates SQL and NoSQL databases, as well as cloud storage, with many data sources. Xplenty allows users to consolidate and manage a range of data with a single mouse click. Anyone that requires a single platform for data integration will find it useful.

Key Features:

  • A drag-and-drop, no-code, or low-code GUI that is simple, intuitive, and easy to use.

  • Connect to over 140 data sources, including databases, data warehouses, and SaaS applications hosted in the cloud.

  • Security, encryption, and data compliance features that are cutting-edge.

  • All of your data is extracted and transformed on the fly, at scale, and is available for analysis.

Cost:

You can request a quote on their website.


3. IBM Db2 Warehouse

IBM Db2 Warehouse is a cloud data warehouse that allows for autonomous data storage and processing scaling. IBM Db2, which includes the Db2 relational database, is a data management software from IBM. Its purpose is to efficiently store, analyze, and retrieve data.

Key Features:

  • Containers that are handled by the client are grouped for easier portability across platforms.

  • Automated scaling and quick and flexible deployment.

  • You'll benefit from elasticity in scalability and the ease with which you may update and upgrade your system.

  • Predictive modeling techniques are incorporated directly into the database with Spark and R open-source, making enterprise AI faster and more efficient.

  • You can convert unstructured data sources into a structured format for analysis with only a few clicks.

Cost:

You can request a quote on their website.


4. Netezza

Netezza, by IBM, is a data warehousing tool. It creates and sells high-performance data warehouse appliances as well as advanced analytics for a variety of data warehouses. It, too, is a versatile and reliable platform with a bundled architecture that includes Netezza core software and analytics within the IBM CloudPak data system.

Key Features:

  • Failure detection and recovery in a timely manner.

  • Existing systems can be upgraded with a single command line.

  • The ability to query many systems at the same time.

Cost:

You can request a quote on their website.


5. Azure Synapse Analytics

Azure Synapse Analytics integrates data integration, big data analytics, and enterprise data warehousing. It employs machine learning technologies for apps and extracts significant insights from any data. By delivering an end-to-end analytics solution, it speeds up project development.

Key Features:

  • Materialized views and a cache of result sets

  • Azure Synapse Analytics performance accelerator for Power BI.

  • Code-free streaming analytics for data warehouse Azure Cognitive Services connection.

  • Private endpoints on a managed virtual network.

  • Security at the column and row levels.

Cost:

You can request a quote on their website.


6. Oracle Autonomous Data Warehouse

Oracle Autonomous Data Warehouse is a cloud-based data warehousing solution that simplifies the process of building a data warehouse, data protection, and the development of data-driven applications.

Key Features:

  • Backup, configuration and patching are just a few of the tasks that can be automated.

  • A comprehensive solution based on a converged database with built-in support for multimodal data and multiple workloads

  • Automatically encrypts data in transit and at rest, secures regulated data installs all security fixes, and detects threats.

Cost:

You can request a quote on their website.


7. IBM Datastage

IBM Datastage extracts, transforms, and loads data from a source system to a target system. It uses an on-premises or cloud-based parallel infrastructure to allow users to integrate data from numerous enterprise systems.

Key Features:

  • Organize and control the data and analytics life cycle.

  • By enhancing ETL performance, you can process data at scale.

  • To see how data travels through transformation and integration, use data lineage.

  • To transport data across numerous cloud sources and data warehouses, employ prebuilt connectors and stages.

Cost:

You can request a quote on their website.


8. MariaDB

MariaDB was designed by the original MySQL developers and is completely open-source. For working with different RDBMS data sources, MariaDB includes a good selection of storage engines, as well as improved storage engines.

Key Features:

  • It is compatible with a wide range of operating systems and programming languages.

  • Any data operating statement will be executed faster with MariaDB's Memory Storage engine than with MySQL's standard storage engine.

  • supports a large number of commands as well as NoSQL-friendly interfaces.

Cost:

This tool is available for free.


9. Panoply

Panoply is a cloud data platform that lets users sync, save, and retrieve their data from anywhere. It automates all data preparation operations to enable end-to-end data management. It reduces the time it takes to integrate, manage, and convert data by eliminating the need for coding and development.

Key Features:

  • Data connectors that don't require any coding and require no upkeep.

  • For any data source, you have complete control over the tables you store.

  • User rights at the table level for fine-grained control.

Cost:

Packages start at $399.


10. Amazon Redshift

Amazon Redshift is a simple, fast, and effective Data Warehousing tool that allows you to examine data using existing Business Intelligence tools using simple SQL queries. It uses methods including high-performance computing, parallel execution, uniform query optimization, and columnar storage to run sophisticated analytical queries.

Key Features:

  • Produce compelling reports and dashboards after effectively conducting high-performance queries on petabytes of semi-structured and structured data.

  • Acquire real-time operational insights, combine structured data from your data warehouse with semi-structured data from your S3 data lake, such as application logs.

  • For secure and governed collaboration on live data, share data both inside and outside your business.

Cost:

Packages start at $0.25 per hour.


11. Google BigQuery

Google BigQuery is a cloud-based serverless data warehouse solution. It saves vast volumes of data and communicates with the database using SQL-Structured Query Language, a programming language. It is effective at extracting information from a large amount of data. It allows for automatic data transfer and full access to the data saved.

Key Features:

  • For online prediction, export ML models to Vertex AI or your own serving layer.

  • Using conventional SQL and a familiar interface, you can easily answer questions and share findings across your datasets from a single pane of glass.

  • Includes an in-memory analysis service that allows users to interactively analyze large and complex datasets with sub-second query response times and high concurrency.

Cost:

You can request a quote on their website.


12. Microsoft Azure

Microsoft Azure is a cloud computing service that allows developers to create, test, deploy, and manage applications and services using Microsoft-managed data centres. Azure is a public cloud computing platform that provides Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) among other services (SaaS).

Key Features:

  • Managed Kubernetes allows you to build and grow apps.

  • Serverless computing can be used to trigger codes.

  • With a boundless analytics service, you can get unrivaled time to insights.

Cost:

You can request a quote on their website.


13. Snowflake

Snowflake is an analytical Data Warehousing Tool that offers a framework that is faster, easier to use, and more adaptable than a traditional data warehouse. Because Snowflake is totally cloud-based, it has a complete SaaS (Software as a Service) architecture.

Key Features:

  • Discover and securely exchange live controlled data throughout your organization, with customers and partners.

  • To comply with data privacy standards like GDPR and CCPA, unify your data warehouses, data lakes, and other segregated data.

  • To help your organization grow, develop new revenue streams based on data.

Cost:

You can start for free.


14. Oracle

Oracle is regarded as one of the top data warehouse software solutions because it optimizes the storage, configuration, and scaling of large amounts of data for analysis and business forecasting. It contains a lot of functions, and users can customize it to their liking.

Key Features:

  • Allows you to create and execute a variety of applications in a scalable, secure, highly available, and high-performance environment.

  • With quarterly upgrades across your whole organization, you'll get a modern user experience and constant innovation.

  • Learn about the future of data management and how to boost data performance with automation, a platform for next-generation apps, database consolidation, and improved data security.

Cost:

You can start for free.


15. Micro Focus Vertica

Micro Focus Vertica is a big data analytics platform built for data warehouses and other big data workloads where speed, scalability, simplicity, and openness are key for success. It's a self-monitored MPP database with scalability and flexibility unlike anything else on the market.

Key Features:

  • To improve processing performance, it includes a full range of Machine Learning algorithms for categorization, overfitting, and prediction.

  • Support for new data-preparation functions that help you get more out of your data while also increasing the quality of your analysis.

  • The production deployment of Machine models is made easier by a streamlined end-to-end approach.

Cost:

Free trial version available.


16. PostGRESQL

PostgreSQL is a popular open-source data warehouse tool that uses its built-in features and analytics tools to store, integrate, and analyze data. Multiple languages can be used to create procedures and functions. (PL/python, pgSQL, etc.) It's a low-cost, easy-to-use, and effective data warehousing solution.

Key Features:

  • Create custom data types, write custom functions, and even write code in various programming languages without having to recompile your database.

  • Many of the SQL standard's features are supported, however with somewhat different syntax or functionality in some cases.

  • PostgreSQL is extremely extensible: many functionalities, like indexes, have documented APIs, allowing you to extend PostgreSQL to solve your problems.

Cost:

This tool is available for free.


17. Amazon DynamoDB

Amazon DynamoDB is a key-value and document database that delivers performance in single-digit milliseconds. It's a fully managed, multi-region, multi-active, persistent database for internet-scale applications with built-in security, backup and restores, and in-memory caching.

Key Features:

  • Provides constant, single-digit millisecond response rates at any size, supporting some of the world's largest scale applications.

  • There are no servers to provide, patch, or manage, and no software to install, maintain, or operate in a serverless environment.

  • By default, all data is encrypted, and all of your tables have a fine-grained identity and access control.

Cost:

You can request a quote on their website.


18. Teradata

Teradata is a subscription-based enterprise software platform that develops and distributes database analytics tools. It enables the unification of various types of data and the deployment of a hybrid multi-cloud platform. This means that deployments can be done on-premises as well as in public clouds like AWS, Azure, and Google Cloud.

Key Features:

  • Richer insights come from a 360-degree view of your entire business, which is integrated from all data sources.

  • By automatically storing the most frequently used data in memory, you can get the performance of in-memory databases without the cost.

  • Availability and performance are mission-critical.

Cost:

You can request a quote on their website.


19. SAS Cloud

SAS Cloud is a statistical program that can be used for data management, advanced analytics, business intelligence, predictive analysis, and multivariate analysis. SAS data warehouse enables users to store and transform large amounts of data into an understandable format. SAS-managed data allows users to access data from anywhere in the world without any problems.

Key Features:

  • You simply register, log in, and get to work on your analytic problems. No installation is required.

  • Create and manage cloud services and solutions in SAS's cloud, your cloud, or on-premises.

  • There is no need to purchase a software license or infrastructure with SAS Results.

Cost:

You can request a quote on their website.


20. Amazon S3

Amazon S3 is a type of object storage that can store and retrieve any amount of data from any location. It's a simple storage solution with industry-leading durability, accessibility, performance, security, and practically limitless scalability at a low cost.

Key Features:

  • Without prior investments or resource procurement cycles, scale your storage resources up and down to match shifting demands.

  • By storing data across the S3 Storage Classes, you can save money without sacrificing speed.

  • With encryption capabilities and access management tools, you can store your data in Amazon S3 and protect it from illegal access.

Cost:

You can request a quote on their website.


21. MarkLogic

MarkLogic Data Hub Service connects and curates your company's data to deliver immediate business benefits. It's multi-model, elastic, transactional, secure, and developed for the cloud, and it runs on a NoSQL basis for speed and scale.

Key Features:

  • Data integration is flexible, allowing you to load data as-is from any source and do real-time data discovery.

  • To enhance, harmonize, and master data more easily and quickly, rely on smart and automated capabilities.

  • There's no need to wait for ETL to finish; developers may start using data services right away. For agile development, it's agile DataOps.

Cost:

You can try this tool for free.


22. SAP Data warehouse Cloud

SAP Data Warehouse Cloud is for small and large organizations. It is essentially an analytic and consumer-centric data cloud. It is built on SAP HANA Cloud's in-memory computing capabilities, which merges SAP and non-SAP data for real-time insights and provides an enterprise-ready data warehouse with end-to-end functionality.

Key Features:

  • In real-time, connect data from many cloud and on-premise repositories.

  • Connect, model, visualize, and exchange data securely in an IT-governed environment using a virtual workspace and no-code environment.

  • Insights on real-time data and in-memory analysis of various sorts of structured, unstructured, and geographic data

  • With a pre-integrated database, data warehouse, data intelligence, data lake, and analytics capabilities, you can get started faster.

Cost:

You can request a quote on their website.


23. Cloudera

Cloudera is the industry's first enterprise data cloud or multi-functional analytics built on a platform that breaks down silos and accelerates the creation of data-driven insights. In shared data instances, it applies consistent security, governance, and metadata.

Key Features:

  • Quickly manipulate data, create new reports and workloads, and access interactive dashboards without involving the IT department.

  • To satisfy corporate needs, eliminate the inefficiencies of data silos by integrating data marts into a Climbable analytics platform.

  • Construct and deploy AI solutions at scale in a cost-effective manner.

Cost:

You can try this tool for free.


24. Informatica

Informatica is a data integration and management technology from Informatica Corporation that is used to get business insights. The metadata information is saved in the repository. The information contained in the destination systems, source systems, and transformations is referred to as metadata information.

Key Features:

  • Create, implement, and manage sophisticated APIs with ease. Connect and integrate your data across any application.

  • To enable your analytics, improve customer experience, and accelerate cloud modernization, deliver reliable, controlled data.

  • With the market-leading, cloud-native ETL and ELT solution from the pioneer in ETL, you can ingest, integrate, and cleanse your data.

Cost:

This tool is available for free.


25. Tableau Data Management

Tableau Data Management can link to a variety of data warehouses, allowing developers to layer data in their visualizations. It offers a user-friendly interface that works well with huge databases.

Key Features:

  • Gives you the visibility and control you need to build trust in your data.

  • With a data management option designed just for and by Tableau, you can get even more out of your data and analytics environment.

  • By operationalizing and automating your data management, you may enable self-service data prep and analytics with more simplicity.

  • Ensures that the right data is being used for analysis.

Cost:

You can request a quote on their website.


26. MongoDB

MongoDB's document data model supports JSON by default, and its expressive query language is simple to understand and use for developers. Automatic failover, horizontal scaling, and the ability to assign data to a specific place are all built-in features.

Key Features:

  • Performance optimization with auto-scaling, actionable recommendations targeted to your individual workloads.

  • With a strong query API that covers operational, transactional, full-text search, and real-time analytics workloads, you can simplify your data architecture.

  • Provides extensive data security and privacy protections as well as mission-critical database administration.

Cost:

Paid services start at $57 per month.


27. Talend

Talend boasts its portfolio as delivering data integration of many forms, with an open-source component - this is a key tool for a data warehouse. The Talend Open Studio can be downloaded for free.

Key Features:

  • Integration of data

  • Integrity and governance of data

  • Integration of applications and APIs

  • Talend Trust Score is the engine that drives this site.

  • Cloud, multi-cloud, and hybrid setups are all supported.

Cost:

You can request a quote on their website.


Things to Consider When Selecting a Data Warehouse Tool

1. Compatibility with your current system

It doesn't matter how powerful a data warehouse technology is if it isn't tailored to your company's needs. Is the data warehouse technology optimiZed for the sorts of data you have, such as structured or unstructured data? Is the required maintenance feasible with the personnel you have on hand?

2. Cost

Pricing in the data warehouse industry, like the whole data warehouse market, is a complex topic. If you get the same hourly rate from two separate vendors, their services could be completely different.

One may excel at machine learning, while the other has concentrated on, for example, providing the greatest number of features. Hence, it is essential to identify your key requirements and choose a tool that fulfills them rather than simply going for the cheaper option.


Conclusion

We've seen some of the greatest data warehouse automation solutions in action. The size of the data being uploaded and the number of queries being run to manage and monitor data play a crucial role in determining the optimal data warehouse technology.

You can choose the one that fits your requirements perfectly.


FAQs

What is a Data Warehouse?

A data warehouse is a database that is designed to store large amounts of disparate data. The data in a data warehouse is contributed by all departments.

Data from several departments, such as finance, customer service and marketing, and sales, are gathered in a single centralized location known as a data warehouse. It allows a business to organize and process data so that it can be analyzed.

How do Data Warehouses Help?

Data warehousing tools are used by businesses for the following purposes:

  • To gain strategic and operational knowledge

  • Decision-making and support mechanisms can be expedited.

  • Examine and assess the effectiveness of marketing campaigns.

  • Examine the performance of your employees.

  • Keep an eye on consumer trends and forecast the next business cycle.

How do Data Warehouse Tools function?

Data warehousing is based on a three-step process: extract, transform, and load (ETL). Relevant data is extracted from the source system using this method. The data quality is fixed and altered after extraction to ensure that it is compatible with use in a corporate data warehouse.

Finally, the data has been loaded and is ready to be monitored, analyzed, and examined in order to improve and evaluate the product.

27 Best Data Warehouse Tools
StartupStash Team

The world's biggest online directory of resources and tools for startups and the most upvoted product on ProductHunt History.