What is Hevo Data?

As an Indian startup scales, its data becomes heavily fragmented. The marketing team has acquisition cost data trapped in Google Ads. The sales team has CRM data trapped in HubSpot. The finance team has revenue data trapped in Razorpay. The product team has behavioral data trapped in Mixpanel.

If the CEO asks, "What is the ROI of our Facebook Ads based on actual finalized Razorpay settlements minus refunds?", answering that question requires a data engineer to write custom Python scripts connecting three different APIs. Those APIs break constantly, causing data outages.

Hevo Data is a No-Code ELT (Extract, Load, Transform) platform that fixes this. You do not write scripts. You log into Hevo, authenticate your Facebook Ads account and your Razorpay account, and Hevo automatically extracts all that data every 5 minutes and dumps it cleanly into a central Google BigQuery or Snowflake data warehouse. From there, a tool like Metabase can read it to give you the exact ROI chart.

6 Key Features That Matter

Hevo's value proposition lies in removing the maintenance burden from your data engineering team.

1. 150+ Plug-and-Play Connectors: It connects natively to almost every major database (PostgreSQL, MongoDB, MySQL) and SaaS application (Salesforce, Stripe, Zendesk, Jira).
2. Near Real-Time Syncing: While many legacy pipelines update data via batch jobs once every 24 hours, Hevo is capable of micro-batching, syncing data from source to destination as fast as every 5 minutes.
3. Auto-Schema Mapping: This is a massive timesaver. If an engineer adds a new column (like user_kyc_status) to your production Postgres database, Hevo automatically detects the schema change and adds the corresponding column to your Snowflake warehouse without the pipeline breaking.
4. In-Flight Transformations: Before the data lands in your warehouse, you can use Hevo's drag-and-drop interface (or Python snippets) to clean the data. For example, hashing sensitive PII (like plain-text email addresses) before it reaches the analytics warehouse.
5. Reverse ETL (Hevo Activate): Hevo doesn't just pull data into the warehouse; it can push it back out. If your data science team runs a model in BigQuery identifying "Users likely to churn," Hevo Activate can push that specific user list back into Intercom or CleverTap to trigger a retention campaign.
6. Alerts & Monitoring: Comprehensive Slack and email alerting if an API endpoint goes down or a data sync stalls, ensuring data teams are never caught off-guard.

Pricing Breakdown (INR Context)

Hevo Data charges based on "Events" (a row of data synced). Their pricing is highly transparent compared to enterprise legacy tools. Note: Converted at 1 USD = ₹84. Excludes 18% GST.

• Free Tier: ₹0. Perfect for early-stage evaluation. Includes 1 Million initial events per month and access to over 50 free connectors (like Postgres and basic SaaS apps).
• Starter: ~₹20,000/month ($239/mo). Includes 5 Million events per month and access to all 150+ premium connectors. Additional events can be purchased dynamically as you scale.
• Business: Custom Pricing. For massive unicorns requiring billions of rows synced, dedicated VPC deployments, and HIPAA/SOC2 strict compliance SLAs.

Who Should Use Hevo Data?

Mid-market to Series B Indian startups that are migrating away from querying a single production database and are actively setting up a proper Modern Data Stack (e.g., pulling everything into Google BigQuery or Amazon Redshift).

It is specifically built for companies that want to empower a Data Analyst to build pipelines without having to beg a Backend Software Engineer for API integration tickets.

Who should NOT use it: Pre-seed startups with very simple data needs. If all your data lives in one Postgres database and you just want to visualize it, use Metabase directly. You don't need a pipeline tool until your data is fragmented across multiple third-party SaaS platforms.

First 5 Setup Steps for Data Teams

Setting up Hevo is remarkably fast, often taking less than 30 minutes to see the first row of data flow.

1. Configure the Destination: In the Hevo dashboard, authenticate your Data Warehouse (e.g., provide the service account credentials for Google BigQuery).
2. Configure the Source: Select a connector (e.g., PostgreSQL). Provide the Read-Replica database credentials and whitelist Hevo's IP addresses.
3. Select Objects to Sync: Hevo will read the source schema. You check the boxes for the specific tables you want to move (e.g., users, transactions), unchecking tables you don't need to save on event costs.
4. Set the Schedule: Choose the sync frequency. For non-critical marketing data, set it to 12 hours. For critical transaction data, set it to 15 minutes.
5. Monitor the Historical Load: Hevo will initiate a historical backfill, bringing all past data into the warehouse, before switching to incremental syncs for new data.

Top Alternatives in the Indian Market

• Fivetran: The absolute global market leader in ELT. Fivetran is incredibly reliable, but it is notoriously expensive for high-volume startups. Hevo is frequently chosen in India simply because it offers 90% of Fivetran's reliability at a much friendlier price point.
• Airbyte: The open-source challenger. Airbyte allows you to self-host the pipeline infrastructure for free. It is highly customizable, but requires significant engineering effort to maintain, upgrade, and debug when connectors break.
• Stitch Data (Talend): A solid mid-market alternative, though many users report their UI and customer support lag behind Hevo's dedicated focus.