Best Data Warehouse Solutions for Medium-Sized Businesses - Page 2

How Many Data Warehouse Solutions Products Does G2 Track?

Total Products under this Category: 153

Category Stats (Nov 2026)

  • Average Rating: 4.38/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Synopsis (+0.77%) - Among all products in this category, Synopsis recorded the largest rating increase compared to last month

Last updated: November 01, 2026

How Does G2 Rank Data Warehouse Solutions Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 8,000+ Authentic Reviews
  • 153+ Products
  • Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

G2 Grid® for Data Warehouse Solutions

G2 Grid® for Data Warehouse Solutions plotting products by satisfaction and market presence

Highlighted products: Databricks, Snowflake, Google Cloud BigQuery, IBM watsonx.data, Amazon Redshift, SAP Datasphere, Cloudera, and SQL Server 2019.

Underlying data: [Grid® JSON](https://www.g2.com/categories/data-warehouse/grids.json?focus%5B%5D=databricks&focus%5B%5D=snowflake&focus%5B%5D=google-cloud-bigquery&focus%5B%5D=ibm-watsonx-data&focus%5B%5D=amazon-redshift&focus%5B%5D=sap-datasphere&focus%5B%5D=cloudera&focus%5B%5D=sql-server-2019&segment=mid-market)

Panoply

Panoply makes it easy to sync, store, and access your data from any data source. Panoply’s easy-to-use, low-maintenance solution unlocks sophisticated analytics without complex data engineering and coding: Key features of the Panoply platform include: -Code-free data integrations for seamless syncing -Automated data warehouse configuration -A powerful workbench for SQL-based data exploration and visualization - In-platform dashboards and reporting -Connections to all major BI and analytical tools -Industry-leading onboarding and support Learn more at https://www.panoply.io

Average Rating: 4.5/5.0

Total Reviews: 80

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How Do G2 Users Rate Panoply?

  • Ease of Use: 8.9/10 (Category avg: 8.8/10)
  • Data Governance: 7.8/10 (Category avg: 8.4/10)
  • Data Security: 8.7/10 (Category avg: 8.8/10)
  • Scalability: 8.1/10 (Category avg: 8.5/10)

Who Is the Company Behind Panoply?

  • Seller: Panoply
  • Year Founded: 2015
  • HQ Location: San Francisco, CA
  • LinkedIn® Page: www.linkedin.com
    13 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 47% Small, 43% Medium

What Do G2 Reviewers Say About Panoply?

AI-generated summary from verified user reviews

Pros
  • Users praise the helpful and responsive customer support at Panoply, facilitating smooth troubleshooting and guidance.
  • Users appreciate the ease of use of Panoply, praising the team's responsive support for troubleshooting and setup.
  • Users value the helpful integrations of Panoply, receiving prompt assistance with setup and troubleshooting.
Cons
  • Users desire the code review features in Panoply's workbench, similar to those in the big query portal.

What Are Recent G2 Reviews of Panoply?

What Are G2 Users Discussing About Panoply?

lyftrondata

Your ultimate next-gen agile, data delivery platform with modern cloud data warehouse & lake. Create and manage all of your data workloads on one platform. Boost the productivity of your data professionals and shorten your time to value in order to deliver modern and integrated data solutions swiftly from anywhere in your organization. We build the best data models around various source API’s, to ensure you will get all of your data and can query the non relational source like API/Json/XML with ANSI Sql. Move on if you data platform is not moving you forward with Lyftron govern and secure data delivery platform for your data migration and modernization needs as Lyftron eliminates traditional ETL/EDW bottlenecks with automatic data pipeline & modern next-gen cloud warehouse which makes data instantly accessible to BI user with the modern cloud compute of Spark & Snowflake. Lyftron connectors automatically convert any source into normalized, ready-to-query relational format and provide search capability on your enterprise data catalog. At Lyftron Data, we eliminate the time spent by engineers building data pipelines manually- and make data instantly accessible to analysts by providing real-time access to all your data with simple ANSI SQL. Our pre-built connectors automatically deliver data to warehouses in normalized, ready-to-query schemas and provide data governance and sensitive data encryption capability.

Average Rating: 4.9/5.0

Total Reviews: 131

How Do G2 Users Rate lyftrondata?

  • Ease of Use: 9.9/10 (Category avg: 8.8/10)
  • Data Governance: 10.0/10 (Category avg: 8.4/10)
  • Data Security: 10.0/10 (Category avg: 8.8/10)
  • Scalability: 10.0/10 (Category avg: 8.5/10)

Who Is the Company Behind lyftrondata?

  • Seller: Lyftron
  • Year Founded: 2019
  • HQ Location: Reston, Virginia
  • LinkedIn® Page: www.linkedin.com
    125 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Architect, Data Analyst
  • Top Industries: Information Technology and Services, Health, Wellness and Fitness
  • Company Size: 84% Medium, 11% Small

What Are Recent G2 Reviews of lyftrondata?

What Are G2 Users Discussing About lyftrondata?

Zap Data Hub

Zap Data Hub is a data warehouse automation solution that streamlines the extraction, loading and transformation (ELT) of ERP and business data into a centralized, governed warehouse for reporting and analytics. Zap Data Hub is used by finance, operations and IT teams who need a faster, more structured way to integrate ERP data from platforms such as Microsoft Dynamics 365, SAP Business One, Sage and SYSPRO alongside other business sources like CRM, payroll and inventory systems. It automates the heavy lifting involved in data integration and preparation, allowing businesses to build a trusted data foundation without extensive coding or manual processes. By automatically mapping, transforming and loading data into a warehouse, Zap eliminates reliance on spreadsheets, manual extracts and disconnected reporting. It creates a governed semantic model that ensures consistent metrics across tools like the Power BI integration, Excel add-in and browser-based reporting. Zap can be deployed in the cloud or on-premises, with support for Microsoft Fabric. Key features and value points • End-to-end data warehouse automation that structures and governs data from ERP and other business systems • Pre-built ERP connectors and models that accelerate deployment and reduce implementation effort • Governed semantic model that ensures consistent, trusted reporting across business units and analytics tools • Reporting support through the Excel add-in, Power BI integration and browser-based options • Deployment flexibility offering cloud-based or on-premises options • Future-ready architecture that integrates with Microsoft Fabric and supports evolving analytics needs Zap Data Hub is suited to organizations that want to automate their reporting data foundations, improve governance and drive business insights without the complexity of manual data engineering.

Average Rating: 4.3/5.0

Total Reviews: 44

How Do G2 Users Rate Zap Data Hub?

  • Ease of Use: 8.0/10 (Category avg: 8.8/10)
  • Data Governance: 7.6/10 (Category avg: 8.4/10)
  • Data Security: 7.7/10 (Category avg: 8.8/10)
  • Scalability: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Zap Data Hub?

  • Seller: ZAP
  • Year Founded: 2001
  • HQ Location: Brisbane, Australia
  • LinkedIn® Page: www.linkedin.com
    87 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Oil & Energy, Computer Software
  • Company Size: 61% Medium, 28% Large

What Do G2 Reviewers Say About Zap Data Hub?

AI-generated summary from verified user reviews

Pros
  • Users praise the ease of use of Zap Data Hub, emphasizing effortless data integration and real-time access.
  • Users value the easy data integration with Zap Data Hub, simplifying ETL processes and enhancing operational efficiency.
  • Users appreciate the excellent customer support from the Zap Team, enhancing their overall experience and satisfaction.
  • Users value the clean reporting functionality of Zap Data Hub, appreciating its seamless integration and time-saving capabilities.
  • Users appreciate the robust analytics capabilities of Zap Data Hub, enabling seamless data integration and BI reporting.
Cons
  • Users find the steep learning curve of Zap Data Hub challenging, requiring support for comfortable usage and report development.
  • Users face complexity challenges when connecting to live Excel data and performing certain calculations effectively.
  • Users face challenges with importing Excel data, particularly with live connections and large file management.
  • Users face challenges with connecting to Excel sources and report exports, affecting overall usability of Zap Data Hub.
  • Users note a steep learning curve, making it challenging for occasional users to navigate and utilize effectively.

What Are Recent G2 Reviews of Zap Data Hub?

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Dremio

Dremio is the pioneer of The Agentic Lakehouse—the only data platform built for agents, managed by agents. Organizations need to transform ideas into actions at unprecedented speed—Dremio delivers this agility by equipping AI agents with federated data access, unstructured data processing, and rich business context through its AI Semantic Layer. In the agentic-era, data engineering teams can’t manually tune performance for thousands of users and agents asking unpredictable questions every second. Dremio’s Agentic Lakehouse autonomously manages itself, removing undifferentiated management tasks, allowing engineers to focus on initiatives that drive business results. Dremio’s agentic lakehouse automatically optimizes queries, reorganizes data, and maintains performance at any scale. Dremio is trusted by thousands of global enterprises including Shell, TD Bank, and Michelin, and built on open standards. Dremio co-created Apache Polaris and Apache Arrow, and it's the only lakehouse built natively on Apache Iceberg, Polaris, and Arrow.

Average Rating: 4.6/5.0

Total Reviews: 65

How Do G2 Users Rate Dremio?

  • Ease of Use: 9.2/10 (Category avg: 8.8/10)
  • Data Governance: 8.2/10 (Category avg: 8.4/10)
  • Scalability: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Dremio?

  • Seller: Dremio
  • Year Founded: 2015
  • HQ Location: Santa Clara, California
  • LinkedIn® Page: www.linkedin.com
    357 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Financial Services, Information Technology and Services
  • Company Size: 49% Large, 39% Medium

What Do G2 Reviewers Say About Dremio?

AI-generated summary from verified user reviews

Pros
  • Users find Dremio to be stupidly easy to use, enhancing efficiency in data sharing and visualization.
  • Users value Dremio's seamless integrations with tools like Power BI and Tableau for efficient data management.
  • Users commend Dremio for its impressive performance, accelerating queries and simplifying data collection across multiple sources.
  • Users value the SQL support in Dremio, facilitating seamless data integration and efficient analysis across platforms.
  • Users highlight Dremio's exceptional data management capabilities, simplifying data manipulation and enhancing analytics for informed decisions.
Cons
  • Users find the initial setup complicated and note a steep learning curve for effective implementation of Dremio.
  • Users note that customer support can be slow, occasionally leading to delays in resolving issues and assisting users.
  • Users find the learning curve steep, making it challenging to fully adopt and utilize Dremio effectively.
  • Users find the difficult setup of Dremio to be a time-consuming challenge, hindering their overall experience.
  • Users often find poor documentation frustrating, relying on forums instead of clear resources for configuration details.

What Are Recent G2 Reviews of Dremio?

What Are G2 Users Discussing About Dremio?

Hive

Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL. At the same time this language also allows traditional map/reduce programmers to plug in their custom mappers and reducers when it is inconvenient or inefficient to express this logic in HiveQL.

Average Rating: 4.2/5.0

Total Reviews: 57

How Do G2 Users Rate Hive?

  • Ease of Use: 8.4/10 (Category avg: 8.8/10)
  • Data Governance: 9.0/10 (Category avg: 8.4/10)
  • Data Security: 8.8/10 (Category avg: 8.8/10)
  • Scalability: 7.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Hive?

Who Uses This Product?

  • Who Uses This: Data Engineer
  • Top Industries: Computer Software, Internet
  • Company Size: 55% Large, 35% Medium

What Are Recent G2 Reviews of Hive?

What Are G2 Users Discussing About Hive?

Roghnu

The Ultimate Data Warehouse + Processing Tool Roghnu provides an all-in-one data solution built to simplify enterprise data management. It combines secure cloud storage, data integrations, and powerful reporting into one easy-to-use platform—perfect for teams who need accurate, on-demand insights without IT overhead. As a Sage Tech Partner, we offer deep expertise for Sage Intacct users. We also work with dozens of other applications like PowerBI, Stripe, Hubspot and more to integrate data into one centralized portal. Roghnu empowers growing businesses to streamline operations by centralizing financial and operational data in a single portal." Check out our Sage Intacct Marketplace page for Data Warehousing & Power BI Templates at https://marketplace.intacct.com/MPProvider?pid=a2X0H000000rY6wUAE Highlights: • Secure, centralized data vault with cloud storage • Unified dashboards and customizable reports • Seamless connection to Sage Intacct, PowerBI, Salesforce, and more • Enterprise-grade security (SOC2 Type II, MFA, VPN) • Expert onboarding, support, and scalability from a reliable partner No more fragmented tools or costly infrastructure—just one place for all your data.

Average Rating: 5.0/5.0

Total Reviews: 48

How Do G2 Users Rate Roghnu?

  • Ease of Use: 9.7/10 (Category avg: 8.8/10)
  • Data Governance: 10.0/10 (Category avg: 8.4/10)
  • Data Security: 10.0/10 (Category avg: 8.8/10)
  • Scalability: 10.0/10 (Category avg: 8.5/10)

Who Is the Company Behind Roghnu?

  • Seller: Roghnu
  • Company Website:
  • Year Founded: 2014
  • HQ Location: Tampa, Florida
  • LinkedIn® Page: www.linkedin.com
    19 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Accounting, Hospital & Health Care
  • Company Size: 58% Medium, 31% Small

What Do G2 Reviewers Say About Roghnu?

AI-generated summary from verified user reviews

Pros
  • Users praise Roghnu's excellent responsiveness and reliability, highlighting efficient communication and timely project delivery.
  • Users value the effective collaboration in Roghnu, highlighted by excellent communication and timely project updates.
  • Users value the deployment flexibility of Roghnu, ensuring a smooth go-live process and timely updates.
  • Users value the ease of use of Roghnu, appreciating seamless meeting setups and effective project tracking.
  • Users find the easy setup of Roghnu efficient, allowing for quick issue resolution and streamlined communication.

What Are Recent G2 Reviews of Roghnu?

What Are G2 Users Discussing About Roghnu?

Shalaka Joshi
SJ
Researched and written by Shalaka Joshi
Updated
Reviews & FAQs

Reviews Summary: The Best Data Warehouse Software for Mid-Market Businesses

Thanks to 7124 Data Warehouse software reviews and associated data from users working for mid-size companies, at G2 we have some of the most definitive data on the best Data Warehouse software for the mid-market space. We have identified 20 individual Data Warehouse products offering the features, pricing and support that Mid-Market companies look for when comparing Data Warehouse software and solutions. These reviews are generated using the qualitative and quantitative feedback from G2 members working in mid-size companies and who have used these Data Warehouse software products.

When G2 reviewers submit their Data Warehouse software reviews, they often provide information on the type of company they work for and what market segment they belong to. We break these different market segments into three distinct groups:

  • Small Business Data Warehouse Software Reviews (< 50 employees)
  • mid-market Data Warehouse Software Reviews (51-1,000 employees)
  • Enterprise Data Warehouse Software Reviews (1,001+ employees)

mid-market businesses have their own unique requirements when it comes to Data Warehouse software compared to small or enterprise companies. That is why these individual mid-size company Data Warehouse software reviews are especially helpful when comparing product set up, ease of use and overall cost.

Below you will find FAQs and review snippets for Data Warehouse software products that work well in mid-market environments. These reviews are written by real G2 users working for these Mid-Market companies who have real-world experience with these Data Warehouse software products.

FAQs About Data Warehouse Software for Mid-Market Businesses

Q. What are the best Data Warehouse software products for mid-size businesses, according to G2 reviewers?
  • Databricks - 4.7-stars, 206 reviews (40% from mid-market reviewers)
  • Snowflake - 4.6-stars, 286 reviews (45% from mid-market reviewers)
  • Google Cloud BigQuery - 4.5-stars, 243 reviews (37% from mid-market reviewers)
  • IBM watsonx.data - 4.4-stars, 27 reviews (33% from mid-market reviewers)
  • SAP Datasphere - 4.3-stars, 53 reviews (34% from mid-market reviewers)
Q. What are the least-liked Data Warehouse software products for professionals at mid-size companies, based on the overall G2 rating?
  • Roghnu - 5.0-stars, 25 reviews (56% from mid-market reviewers)
  • Starburst - 4.3-stars, 14 reviews (24% from mid-market reviewers)
  • Hive - 4.4-stars, 20 reviews (35% from mid-market reviewers)
  • Mozart Data - 4.5-stars, 29 reviews (48% from mid-market reviewers)
  • Dremio - 4.5-stars, 17 reviews (37% from mid-market reviewers)
Q. What are the highest-rated Data Warehouse software tool features according to employees at Mid-Market companies?
  • Data Integration - 4.5-stars
  • Cloud - 4.5-stars
  • Scalability - 4.5-stars
Q. What are the features that are rated lowest by employees at Mid-Market companies?
  • AI Text Summarization - 3.8-stars
  • AI Text Generation - 3.8-stars
  • In-Database Machine Learning - 4.1-stars
Q. How many Data Warehouse software reviews are from users working in mid-market companies?

1389 out of all Data Warehouse software reviews on G2 are from users working in Mid-Market companies (19%).

Here's What Reviewers Working at mid-market Businesses Have to Say About Data Warehouse Software

What Mid-Market Professionals Liked What Mid-Market Professionals Disliked

SQL Server 2019: “Using SQL Server is very easy to use and writing queries in TSQL to query the databases is a big part of my work activities. Using the execution plan to inform you of where to add an index is very useful to speed up the queries.”

Read Review

Amazon Redshift: “Cost, Performance, general usability was very lacking. We switched to Aurora because Redshift just wasn't for us.”

Read Review

Panoply: “The platform is *extremely* easy to set up with reliable data ingestion from lots of commonly needed data sources, and where they're missing, the customer support team's work has exceeded our expectations.”

Read Review

Google Cloud BigQuery: “Cons: Resource limits. Because of how Google Cloud BigQuery uses nodes, typical SQL processes involving window functions can fail. We've regularly hit resources exceeded limits on data sets of a few million records, which seems absurd these days. Additionally, BigQuery can struggle with multiple CTEs, leading to us running more queries as tables vs. views. Doing so created greater complexity in orchestration that's a challenge to manage. Limited documentation or help. When we've run into resource limit issues, there has been a lack of support in online articles as well as direct assistance. You have to be on a certain service tier to get a Google employee to help - which we aren't. And there are few to no official posts about how to handle the resource limit issue, so all our knowledge comes from other users who have experienced the same. Given that BigQuery is designed for SQL queries, I cannot recommend it with these significant challenges that have caused my team days of delay.”

Read Review

Databricks: “The unified platform approach is what I appreciate most. Having notebooks, data engineering pipelines, ML workflows, and SQL analytics all in one place saves a ton of time instead of juggling multiple tools. The collaborative notebooks make it easy to share work with teammates, and the cluster management has gotten a lot smoother over time. Delta Lake integration is also a huge plus for keeping our data reliable and consistent.”

Read Review

IBM watsonx.data: “setup and configuration can feel complex, especially for smaller teams without strong data engineering support. It can also become expensive at scale, particularly when handling large workloads or advanced features.”

Read Review
Recommendations To Others Problems Solved & Benefits

Roghnu: “You get what you pay for and Roghnu is well worth the cost. I tried to get items resolved using the Sage Intacct support and I do not always get the best support”

Read Review

Synopsis: “- Helps me work a lot faster by pulling marketing lists for me based on how different segments are interacting with our product - Helps me understand how the business is doing”

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Amazon Redshift: “Excellent performance for very large-scale data sets. Columnar database, unlimited storage at a very affordable price.”

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IBM watsonx.data: “It helps me manage data from different sources in one place, making it much easier to access, organize, and analyze everything. As a result, I save time, and my day-to-day data work feels more efficient, streamlined, and easier to stay on top of.”

Read Review

Amazon Redshift: “If you have a huge data this is the platform for your to build your Data warehouse and most importantly you can save a lot of money.”

Read Review

Databricks: “Solving the real-time data as well as metrics for our campaigns, it's able to process on a nightly basis, which is very helpful.”

Read Review