Neon vs CockroachDB vs TiDB: Distributed SQL Databases Compared

Traditional single-node databases served most applications well for two decades. You picked a Postgres or MySQL instance, scaled it vertically, and added read replicas when queries started to slow down. That approach still works for many products. But if your application needs strong consistency across multiple regions, handles write-heavy workloads that outgrow a single node, or must survive an entire availability zone going offline without manual intervention, you need distributed SQL.

Neon, CockroachDB, and TiDB all claim to solve this problem, but they approach it from completely different directions. Neon is serverless Postgres with a separation of compute and storage that enables branching and autoscaling. CockroachDB is a ground-up distributed SQL database inspired by Google Spanner, built for multi-region resilience. TiDB is a MySQL-compatible distributed database with a hybrid transactional and analytical processing (HTAP) engine that lets you run real-time analytics alongside OLTP workloads.

These are not interchangeable products. Picking the wrong one means either paying for capabilities you do not need or hitting a wall when your requirements outgrow your database's architecture. We have deployed all three in production for clients at Kanopy, and the right choice depends entirely on your workload profile, your team's expertise, and where you expect to be in 18 months.

Understanding the architectural differences between these three databases is the single most important factor in making the right choice. Features and pricing change. Architecture does not.

Neon: Separated Compute and Storage on Postgres

Neon runs standard PostgreSQL (version 17 as of 2030) but replaces the storage layer with a custom, disaggregated architecture. Compute nodes run vanilla Postgres and are completely stateless. Storage lives in a separate tier built on a log-structured merge tree that writes to object storage (S3). This separation is what enables Neon's headline features: instant database branching, scale-to-zero compute, and point-in-time recovery down to the second.

Crucially, Neon is not a distributed database in the traditional sense. It does not shard your data across multiple nodes for horizontal write scaling. A single Neon database still runs on a single compute node (up to 10 CUs as of 2030). What Neon distributes is storage, not compute. This gives you durability and fast branching, but your write throughput ceiling is still bounded by a single Postgres process. For most applications handling fewer than 10,000 write transactions per second, this is more than enough.

CockroachDB: Multi-Active, Geo-Distributed SQL

CockroachDB was designed from the ground up to distribute data across multiple nodes, data centers, and regions. Every node can accept reads and writes. Data is automatically split into ranges (roughly 512 MB chunks), and each range is replicated across at least three nodes using Raft consensus. If a node dies, the surviving replicas continue serving traffic and the cluster automatically re-replicates the data to maintain the replication factor.

This architecture means CockroachDB handles horizontal write scaling natively. Need more write throughput? Add nodes. Need multi-region active-active deployments? Configure locality-aware replication and CockroachDB places data replicas according to your topology rules. The cost of this architecture is latency: every write must achieve consensus across replicas, adding 2 to 10ms of overhead depending on inter-node distance. For geo-distributed deployments spanning continents, that consensus round-trip can push write latency to 100 to 300ms.

TiDB: Distributed SQL with Built-in Analytics

TiDB separates its architecture into three layers. TiDB servers handle SQL parsing and query planning (stateless, horizontally scalable). TiKV handles distributed key-value storage for transactional workloads using Raft consensus, similar to CockroachDB. TiFlash is a columnar storage engine that maintains a real-time replica of your data optimized for analytical queries. The TiDB query optimizer automatically routes queries to TiKV or TiFlash based on the query pattern.

This HTAP (Hybrid Transactional/Analytical Processing) design is TiDB's differentiator. You can run complex aggregation queries, window functions, and joins across billions of rows on TiFlash without impacting your OLTP workload on TiKV. Other databases require you to set up a separate data warehouse (Snowflake, BigQuery, ClickHouse) and build ETL pipelines to sync data. TiDB collapses that entire pipeline into a single system. If your application needs real-time dashboards, reporting, or analytics alongside transactional operations, TiDB eliminates significant infrastructure complexity.

Compatibility with existing database protocols matters because it determines how much of your application code, tooling, and team expertise carries over. A database that claims "compatibility" but breaks your ORM or requires rewriting 30% of your queries is not actually compatible in any meaningful sense.

Neon: Full PostgreSQL Compatibility

Neon runs unmodified PostgreSQL. This is not "Postgres-compatible" in the way some NewSQL databases use the term. It is actual Postgres. Every extension works: pgvector for embeddings, PostGIS for geospatial, pg_trgm for fuzzy search, pg_cron for scheduled jobs, and hundreds more. Every Postgres client library, ORM, and migration tool works without modification. If your code works on RDS Postgres or Cloud SQL Postgres, it works on Neon with zero changes.

This full compatibility is Neon's strongest advantage for teams already invested in the Postgres ecosystem. Prisma, Drizzle, TypeORM, SQLAlchemy, ActiveRecord, Diesel, and every other Postgres ORM work perfectly. Your pg_dump backups restore cleanly. Your Postgres monitoring tools connect without issues. There is zero learning curve beyond Neon's own dashboard and branching features.

CockroachDB: Postgres Wire-Compatible with Caveats

CockroachDB speaks the PostgreSQL wire protocol, so Postgres client libraries and most ORMs connect to it. However, CockroachDB is not PostgreSQL under the hood. It is a custom storage engine with its own SQL implementation that aims for Postgres syntax compatibility. In practice, this means most standard SQL works, but there are gaps.

Extensions are not supported. If your application depends on pgvector, PostGIS, or any other Postgres extension, CockroachDB cannot run it. Stored procedures have limited support. Some Postgres-specific syntax (certain window function forms, advanced CTE features, custom operators) may behave differently or fail. CockroachDB has closed many of these gaps over the years, but you should always test your actual queries against CockroachDB before committing. The team maintains a detailed compatibility tracker that lists known differences.

TiDB: MySQL Wire-Compatible

TiDB speaks the MySQL wire protocol and targets MySQL 8.0 syntax compatibility. MySQL client libraries, connectors, and most MySQL ORMs work out of the box. Laravel, Rails with the mysql2 adapter, Django with the MySQL backend, and Prisma with the MySQL provider all connect to TiDB without changes.

The compatibility is strong but not perfect. TiDB does not support MySQL's FULLTEXT indexes, spatial functions are limited compared to native MySQL, and some rarely used MySQL features (certain lock types, XA transactions) behave differently. Triggers and events have limited support. For the vast majority of CRUD-heavy web applications, these gaps do not matter. If you are running a standard SaaS app on MySQL, migrating to TiDB is straightforward. If you rely on MySQL-specific edge cases, test thoroughly first.

Database pricing is where marketing promises meet production reality. All three vendors offer free tiers and usage-based pricing, but the cost structures are fundamentally different because the underlying architectures are different.

Neon Pricing

Neon charges for compute (measured in compute-hours) and storage (measured in GB-months). The free tier includes 0.5 GB storage, 10 branches, and 1 compute endpoint. The Launch plan at $19/month gets you 10 GB storage, 50 branches, and autoscaling up to 4 CUs. The Scale plan at $69/month provides 50 GB, unlimited branches, and autoscaling up to 10 CUs. Additional compute costs $0.16 per compute-hour. Storage beyond included amounts is $0.024/GB/month.

The key cost advantage of Neon is scale-to-zero. If your database is idle (development environments, staging, side projects), compute costs drop to zero. For teams running 10 to 20 preview environments alongside production, this saves hundreds of dollars per month compared to always-on alternatives. The key cost risk is unpredictable compute usage. A long-running analytics query or a traffic spike can burn through compute-hours fast.

CockroachDB Pricing

CockroachDB Serverless (their managed cloud offering) charges based on Request Units (RUs) and storage. The free tier includes 10 million RUs/month and 10 GB storage. The Basic plan starts at $0 with pay-as-you-go pricing: $1 per 10 million RUs and $0.50/GB/month for storage. The Standard plan adds dedicated compute starting at roughly $300/month per node for production workloads that need predictable performance. Enterprise pricing (self-hosted or dedicated clusters) starts around $1,000/month and scales based on cluster size.

CockroachDB's RU-based pricing can be opaque. A single SQL query might consume 1 RU or 1,000 RUs depending on the number of rows scanned, the number of regions involved, and whether the query triggers cross-range transactions. For teams building their first application on CockroachDB, the Serverless tier is genuinely cheap. For production multi-region deployments, expect to spend $500 to $3,000/month depending on throughput and replication topology.

TiDB Pricing

TiDB Cloud (the managed offering from PingCAP) offers a Serverless tier with 25 GB of row storage, 25 GB of columnar storage, and 250 million Request Units per month for free. The Dedicated tier starts at roughly $400/month for a minimal production cluster (2 TiDB nodes, 3 TiKV nodes) and scales linearly with the number of nodes. Columnar storage for TiFlash (the HTAP engine) adds additional cost per node, starting around $200/month per TiFlash replica.

TiDB's pricing reflects its more complex architecture. You are paying for three separate layers (TiDB compute, TiKV storage, TiFlash analytics), each of which scales independently. This gives you fine-grained control but also makes cost estimation harder. If you are using TiDB primarily as a transactional database without TiFlash, costs are comparable to CockroachDB. If you are leveraging the HTAP capability, you are paying for TiFlash nodes but potentially saving the cost of a separate analytics warehouse.

Cost Comparison for a Mid-Stage SaaS

For a SaaS application with 50 GB of data, 5,000 transactions per second, and single-region deployment: Neon runs roughly $150 to $200/month on the Scale plan with moderate compute usage. CockroachDB Serverless runs roughly $100 to $250/month depending on RU consumption. TiDB Cloud Serverless handles this within the free tier for low-throughput scenarios, or $400 to $600/month on Dedicated for guaranteed performance. The cost picture shifts dramatically at multi-region scale. For details on when scaling decisions become critical, our database scaling guide covers the inflection points.

Benchmarks in isolation are misleading. A database that delivers 1ms reads on a single node might deliver 50ms reads in a geo-distributed configuration. What matters is performance under your specific deployment topology.

Single-Region Performance

In a single-region deployment, Neon wins on simple query latency. It runs vanilla Postgres with no distributed coordination overhead. Point reads return in 1 to 3ms. Simple inserts complete in 2 to 5ms. Complex joins and aggregations run at native Postgres speed with the full query optimizer available. If your application runs in a single region and your data fits on a single node, Neon's performance is effectively unbeatable because there is no distribution tax.

CockroachDB in a single-region cluster adds 2 to 5ms of overhead per write due to Raft consensus across replicas. Reads from the leaseholder node are fast (2 to 4ms), but follower reads add latency. For read-heavy workloads, CockroachDB's single-region performance is competitive. For write-heavy workloads, the consensus overhead is noticeable compared to a single-node Postgres instance.

TiDB's single-region performance sits between the two. TiKV's distributed storage adds 3 to 8ms per write due to Raft consensus. Reads are fast at 2 to 5ms for simple key lookups. Where TiDB excels in single-region deployments is analytical queries: TiFlash can process aggregations over hundreds of millions of rows in seconds, something neither Neon nor CockroachDB can match without external tooling.

Multi-Region Performance

This is where the architectural differences become stark. Neon does not natively support multi-region active-active deployments. You pick a region for your database, and that is where your writes go. Read replicas in other regions are on the roadmap, but as of 2030, Neon is primarily a single-region database. You can pair it with application-level caching or a CDN for global reads, but writes always route to the primary region.

CockroachDB was built for multi-region from day one. You can configure regional tables (data pinned to specific regions for low-latency local reads/writes), global tables (replicated everywhere for fast reads with slower writes), and regional-by-row tables (each row lives in the region of the user who owns it). A user in Frankfurt reads their data from a Frankfurt replica in 2 to 5ms. A user in Virginia reads from a Virginia replica in 2 to 5ms. Cross-region writes incur the consensus round-trip, typically 80 to 200ms depending on geographic distance.

TiDB supports multi-region deployments through placement rules that control which TiKV nodes hold which data. The configuration is less automated than CockroachDB's locality-aware features but offers similar capabilities. TiDB's Placement Driver (PD) component manages data distribution and can pin ranges to specific regions. Multi-region TiDB requires more manual configuration but delivers comparable geo-distribution for teams willing to invest in the setup.

Write Throughput Scaling

Neon's write throughput is bounded by a single Postgres instance. At 10 CUs, you can sustain roughly 5,000 to 15,000 write transactions per second depending on transaction complexity. CockroachDB scales writes linearly by adding nodes. A 9-node cluster can sustain 30,000+ write TPS. TiDB similarly scales writes by adding TiKV nodes. Both CockroachDB and TiDB have been proven at over 100,000 write TPS in production at companies like DoorDash (CockroachDB) and ByteDance (TiDB).

One of the most expensive and fragile pieces of modern data architecture is the pipeline that moves data from your transactional database to your analytics warehouse. You set up CDC (Change Data Capture) from Postgres or MySQL, pipe it through Kafka or Debezium, transform it with dbt, load it into Snowflake or BigQuery, and pray that the pipeline does not break at 3 AM. TiDB's HTAP architecture eliminates this entire stack for a significant class of analytics workloads.

How TiFlash Works

TiFlash maintains a columnar replica of your TiKV data in real time. When you write a row to TiDB, it lands in TiKV (row-based, optimized for OLTP). Within seconds, that data is asynchronously replicated to TiFlash in columnar format (optimized for OLAP). The TiDB query optimizer inspects each query and routes it to the appropriate engine. A simple point lookup goes to TiKV. An aggregation scanning millions of rows goes to TiFlash. A mixed query might read from both.

This means you can run a query like "show me revenue by region for the last 90 days, broken down by product category" directly against your production database. On TiFlash, this query scans columnar data with vectorized execution and completes in seconds. On Neon or CockroachDB, the same query would scan row-based storage and either take minutes or time out entirely on large datasets. You would need to replicate your data to a separate analytics engine to get acceptable performance.

When HTAP Matters

HTAP is not a universal requirement. If your analytics are limited to simple dashboards with queries that touch thousands of rows (not millions), any of these three databases handles them fine. HTAP becomes valuable when you need real-time analytics on fresh data (dashboards that reflect transactions from the last 30 seconds), when your analytics queries scan large volumes of historical data, or when maintaining a separate analytics pipeline is eating your engineering bandwidth.

We have seen TiDB's HTAP capability save clients $2,000 to $5,000 per month in combined Snowflake and ETL pipeline costs, plus 10 to 20 hours of monthly engineering time spent maintaining those pipelines. For a series A startup running lean, that is a meaningful savings. For a company already invested in a mature data warehouse with complex transformations, TiDB's built-in analytics are a complement rather than a replacement.

What Neon and CockroachDB Offer Instead

Neon gives you full Postgres, which means you can use Postgres-native analytics extensions and tools. The pg_analytics extension (powered by DuckDB) is gaining traction for running analytical queries directly in Postgres. CockroachDB supports standard SQL aggregations and has improved its analytical query performance significantly, but neither matches TiDB's purpose-built columnar engine for large-scale analytical workloads. For teams that need serious analytics alongside OLTP, TiDB is the only option in this comparison that does not require a separate system. For a broader look at database selection criteria, our serverless database comparison covers adjacent options.

Choosing a database is a multi-year commitment. Migrating away from any distributed database is painful, so it is worth understanding what you are signing up for operationally before you commit.

Migrating to Neon

If you are on any PostgreSQL host (RDS, Cloud SQL, Supabase, self-hosted Postgres), migrating to Neon is straightforward. Use pg_dump/pg_restore for databases under 100 GB. For larger databases, Neon supports logical replication for near-zero-downtime migration. Your application code, ORM configuration, and queries stay exactly the same. You change a connection string and you are done. Migrating away from Neon is equally simple since it runs standard Postgres. Your data is never locked in.

Migrating to CockroachDB

Migrating from Postgres to CockroachDB requires more work. CockroachDB provides an IMPORT tool and supports Postgres-compatible SQL, but you will need to audit your schema for incompatibilities. Auto-incrementing primary keys should be replaced with UUIDs or CockroachDB's unique_rowid() function (sequential IDs create hot spots in distributed storage). Postgres extensions need alternative solutions. Some query patterns may need rewriting. Plan for a 2 to 4 week migration effort for a moderately complex application.

Migrating away from CockroachDB is harder. While CockroachDB speaks Postgres wire protocol, its internal data format is proprietary. You can export data via SQL queries or CSV dumps, but there is no equivalent of pg_dump that preserves your full schema. Plan for significant effort if you decide to leave.

Migrating to TiDB

If you are on MySQL, TiDB provides TiDB Lightning for fast bulk imports and TiDB Data Migration (DM) for continuous replication from MySQL. For many MySQL workloads, migration is smooth. The main gotchas are the same ones that affect any MySQL-to-compatible-system migration: unsupported features like FULLTEXT indexes, certain character set behaviors, and MySQL-specific syntax edge cases. From Postgres, you need a schema conversion step (Postgres SQL to MySQL SQL), which adds complexity.

Migrating away from TiDB to MySQL is relatively straightforward since TiDB stores data in a MySQL-compatible format. Dumpling (TiDB's export tool) produces MySQL-compatible SQL dumps. Migrating to Postgres from TiDB requires the same cross-dialect conversion as any MySQL-to-Postgres migration.

Operational Complexity

Neon is the simplest to operate. It is fully managed with no knobs to tune beyond compute size. There are no replicas to manage, no sharding to configure, no consensus groups to monitor. CockroachDB Serverless is similarly low-ops, but CockroachDB Dedicated or self-hosted clusters require understanding of Raft consensus, range splits, leaseholder placement, and cluster topology. TiDB Cloud Dedicated is the most complex: you are managing three separate components (TiDB, TiKV, TiFlash), each with its own scaling and tuning parameters. The PingCAP team provides good tooling (TiDB Dashboard, Grafana integrations), but the learning curve is steeper than either Neon or CockroachDB.

After deploying all three databases across dozens of production projects, here is our direct recommendation based on workload type.

Choose Neon If

Your application runs in a single region and your data fits on a single node (under 500 GB, under 10,000 write TPS). You want full Postgres compatibility with zero compromises. You value developer experience features like database branching for preview environments and CI/CD. You want scale-to-zero for development and staging environments. You are using Prisma, Drizzle, or any Postgres ORM and just need a fast, reliable connection string. Neon is the best serverless Postgres available today, and for the majority of web applications, Postgres on a single node is all you need.

Choose CockroachDB If

You need multi-region active-active deployments with strong consistency. Your users are distributed globally and you need single-digit-millisecond read latency from every region. You need horizontal write scaling beyond what a single Postgres node can handle. You are building financial services, e-commerce, or any application where surviving a regional outage without data loss is a hard requirement. CockroachDB is the most battle-tested distributed SQL database for these use cases, and nothing else in this comparison matches its geo-distribution capabilities.

Choose TiDB If

You need real-time analytics alongside your transactional workload. You are currently running MySQL and want to scale horizontally without changing your application code. You want to eliminate your ETL pipeline and analytics warehouse for operational reporting. You are processing large volumes of data (billions of rows) and need both fast point queries and fast aggregations. TiDB's HTAP architecture is genuinely unique, and for teams drowning in data pipeline complexity, it can simplify your entire stack.

When to Look Elsewhere

If you need a full backend-as-a-service with auth, storage, and real-time subscriptions baked in, none of these three are the right fit. Look at Supabase instead. If you need a document database for highly variable schema data, consider MongoDB. If your primary need is a data warehouse for batch analytics, Snowflake or BigQuery will outperform all three on pure OLAP workloads.

The most common mistake we see is teams choosing a distributed database because they think they will need it someday. Distributed databases add latency, complexity, and cost. If your application runs in a single region and your data fits on a single Postgres node, start with Neon. You can always migrate to CockroachDB or TiDB later if your requirements genuinely demand distributed architecture. Starting simple and scaling up is always cheaper than starting complex and scaling down.

Not sure which distributed SQL database fits your architecture? Book a free strategy call and our team will evaluate your workload, growth projections, and compliance requirements to recommend the right data layer for your product.