How Much Lock-In Is Too Much? The Real Truth About Avoiding Vendor Lock-In in Data Platforms

Everyone talks about avoiding lock-in, but let’s be real — there’s no such thing as zero lock-in.

🚫 Complete portability is a myth. Even if you choose open formats like Parquet, Iceberg, or Delta, your workflows, governance models, and optimizations will still tie you to a platform’s ecosystem.

Why Are People So Scared of Lock-In Now?

🔹 Databricks? Too much lock-in with Unity Catalog and Delta Live Tables.
🔹 Snowflake? Too proprietary — good luck moving those optimizations elsewhere.
🔹 BigQuery? Try lifting and shifting that without rewriting SQL and governance policies.

People panic about lock-in today, but weren’t we just as locked into Teradata, Oracle, or Hadoop back in the day? We never seemed this scared. So what changed?

What’s REALLY Happening?

1️⃣ Cloud gave us the illusion of flexibility — We assumed multi-cloud would make everything portable, but cloud providers built stickier services than ever.

2️⃣ The ecosystem is now more fragmented — We don’t just pick a database anymore. We pick a catalog, compute engine, storage format, governance model, and pipeline framework — each with its own lock-in risks.

3️⃣ Cost and exit strategy awareness has increased — Companies now understand that getting locked in can mean exponentially rising costs and a painful migration later.

Is Lock-In Really Bad? Or Are We Just Overthinking It?

🔹 Lock-in is bad when:

• You can’t switch platforms without rewriting everything
• Your costs keep increasing, but you have no alternatives
• You get locked into an ecosystem that isn’t innovating

🔹 Lock-in is good when:

• It saves you time and removes complexity (e.g., Delta Live Tables managing infra for you)
• You get a competitive advantage (e.g., Snowflake’s performance optimizations)
• The switching cost is justified by long-term benefits

So, How Much Lock-In Is Okay?

1️⃣ If it saves time, money, or improves performance, some lock-in is worth it.
2️⃣ If it restricts future flexibility without significant upside, reconsider.
3️⃣ If leaving would require a full platform rebuild, that’s too much lock-in.

The Truth? Pragmatic Lock-In is Inevitable. Smart Choices Keep You in Control.

Instead of obsessing over avoiding lock-in completely, we should focus on:
✅ Choosing open storage formats (Iceberg, Parquet, Avro)
✅ Using platforms that support multiple compute engines (Spark, Trino, SQL)
✅ Ensuring interoperability across clouds (Federated query engines, open APIs)