---
title: Modernize Legacy ETL with Hevo’s Automated ELT Software
description: Modernize your data stack by moving from legacy ETL to Hevo’s automated ELT platform—scalable, zero-maintenance, and ready for the cloud.
canonical_url: https://hevodata.com/data-modernization/
content_type: page
word_count: 454
source: https://hevodata.com/data-modernization.md
---

# Modernize Legacy ETL with Hevo's Automated ELT Software

Hevo replaces disconnected, in-house ETL with automated ELT pipelines that centralize data from SaaS tools, databases, and files into one governed destination, giving teams self-serve, trusted data access without routing every request through engineering.

## Key facts

- Rated 4.4/5 on G2 (290+ reviews).
- Used by 2,000+ companies worldwide.
- 150+ pre-built connectors, ready to use with minimal setup.
- Pipelines adapt to schema changes automatically, with no ongoing manual intervention.

## The problem with data silos

When data is spread across disconnected systems, teams struggle to get a consistent view and act confidently on insights:

- Fragmented data sources make consistent reporting difficult.
- The engineering team becomes a bottleneck for every new data request.
- Slow access to insights reduces business agility.
- Manual data sharing increases risk and compliance overhead.
- Conflicting metrics erode trust in analytics.

## Making data accessible and trusted

- **Unified data access:** SaaS tools, databases, and files flow into a single governed destination, so teams work from one source of truth.
- **Reliable analytics foundations:** automated pipelines keep data consistent and stable, so dashboards and reports stay accurate without manual effort.
- **Self-serve analytics:** teams explore and analyze data independently, without relying on engineering for every new question.

## Building in-house vs. buying managed ELT

| Dimension | Build in-house | Buy Hevo ELT |
| --- | --- | --- |
| Initial setup | Months of engineering work | Ready in minutes |
| Reliability | Failures handled manually | Issues detected and handled automatically |
| Self-serve | Data access routed through engineering | Business teams access independently |
| Maintenance | Continuous updates required | Fully automated |
| Data access | Manual and inconsistent | Self-serve with guardrails |
| Governance | Added after the fact | Built in by default |
| Cost | High TCO from unpredictable costs | Transparent and predictable costs |

Talk to sales: https://hevodata.com/schedule-demo/

## How teams enable self-serve data with Hevo

- Connect to 150+ pre-built sources with minimal setup.
- Pipelines automatically adapt to schema changes.
- Data stays up to date without ongoing manual intervention.
- Data access scales with transparent, predictable costs.

## What customers say

- **Ramkumar Natarajan, Senior Manager, Data Operations, ThoughtSpot:** "Hevo delivered zero downtime and unmatched reliability, cut infrastructure costs by 85% and ETL spend by 50%, while boosting data usage by 30 to 35%."
- **Samvit Majumdar, Principal Engineer, Whatfix:** "Before 2018, Whatfix lacked internal analytics. Teams relied on uncorrelated customer data, limiting insights to account-level views and preventing a holistic business perspective."
- **Snehashish Paul, Lead Data Engineer, Zetwerk:** "Without Hevo, Zetwerk would spend weeks manually integrating data. With Hevo, complex sources like QuickBooks are ingested in a single day."

Case study: https://hevodata.com/customers/

## Pricing

Hevo uses transparent, usage-based pricing with no credit card required to start.

## FAQ

### Why do data silos slow down decision making?

When data is spread across disconnected systems, teams struggle to get a consistent view, engineering becomes a bottleneck for every request, and conflicting metrics erode trust in analytics.

### How does Hevo enable self-serve data access?

By centralizing data from 150+ sources into one governed destination, with automated schema handling, so business teams can access trusted data independently instead of routing requests through engineering.

### How does building ELT in-house compare to using Hevo?

Building in-house typically takes months of engineering work, requires manual failure handling and continuous maintenance, and has unpredictable costs. Hevo is ready in minutes, detects and handles issues automatically, and uses transparent, predictable pricing.

### Does Hevo require ongoing manual maintenance to stay accurate?

No. Pipelines automatically adapt to schema changes and stay up to date without ongoing manual intervention.

### Is governance built into Hevo, or added afterward?

Built in by default, unlike in-house pipelines where governance is typically layered on after the fact.