面向开发者的最佳客户数据平台（CDP）对比

The promise of a Customer Data Platform (CDP) is simple: collect data from everywhere, unify it into coherent customer profiles, and pipe it wherever you need it. The reality is that most CDPs were designed for marketing teams running ad campaigns, not developers who care about instrumentation, data quality, and control.

If you're a developer who wants flexible SDKs and APIs, predictable pipelines, raw data access via SQL, and integrations that fit into their existing tooling – not a black box optimized for ad platforms – you're in the right place.

This guide compares the best CDPs for developers to help you collect, unify, query, and move customer data with confidence.

At a minimum, a CDP should include:

• Data collection from multiple sources (web, mobile, server, third-party tools)
• Identity resolution to stitch together anonymous and known users
• Audience segmentation and cohort building
• Integrations with downstream tools (CRMs, ad platforms, email, warehouses)
• Real-time or batch data syncing

The best CDPs go further and give you analytics capabilities so you can actually answer questions with your data:

• Event-based tracking, with full control over your data schema
• Funnels, retention, and cohort analysis, to understand user journeys
• Session replay and behavioral context, to see what users actually did
• SQL access and raw data exports, for custom queries and external tooling
• Data warehouse integration, so your CDP works with (not against) your existing stack
• Privacy-first design, to stay GDPR/CCPA compliant without extra work

Here's how some of the most popular CDPs compare:

You might notice some absences: Salesforce Data Cloud, Adobe Real-Time CDP, and Treasure Data are all major enterprise players. They're powerful, but they're also designed for large marketing orgs with dedicated implementation teams and big budgets to match.

This guide focuses on tools that developers can actually evaluate, set up, and get value from without a long-winded implementation project.

1. PostHog

PostHog takes a different approach to customer data: instead of being a CDP that bolts on analytics, it's an all-in-one platform where CDP functionality works together with product analytics, web analytics, session replay, feature flags, experiments, error tracking, LLM observability, surveys, and more natively.

PostHog's data pipeline provides full CDP capabilities through three core components:

• Sources: Ingest data from 20+ managed sources (Stripe, Hubspot, Salesforce, Snowflake, BigQuery, Google/Meta/LinkedIn/TikTok Ads, and more) or self-managed object storage (S3, GCS, Azure Blob). Data syncs automatically and can be joined with your product analytics data using the built-in data warehouse.
• Transformations: Clean and transform event data in real-time before it's stored – including GeoIP enrichment, PII scrubbing, bot filtering, property standardization, and custom transformations written in Hog. Transformations are completely free with no volume limits.
• Destinations: Send data to dozens of tools in real-time or schedule batch exports to warehouses like Snowflake, BigQuery, Redshift, Postgres, and Databricks.

Beyond data pipelines, PostHog's CDP also handles event capture from client-side SDKs and server-side APIs and, unlike standalone CDPs, all that data is immediately available for analysis – no export required. Every event, user, and session can be queried with SQL, visualized in funnels and retention charts, or connected to a specific session recording. You can build cohorts based on behavior, run experiments on segments, and see exactly what users did before churning – all in one place.

PostHog uses simple usage-based pricing with a generous free tier, so you can start collecting and analyzing data before committing to a long-term contract.

Strengths:

• CDP and analytics in one platform
• Event-based insights, funnels, and retention built in
• SQL access and raw data ownership
• Flexible destinations and transformations
• Strong developer tooling and APIs

Community:

• PostHog is fully open source under the MIT license, actively maintained on GitHub.
• The repository has 30k+ stars, 400+ contributors, and daily commits
• Development happens in public

PostHog is best for...

Developers who want a CDP that doesn't stop at data plumbing – and teams that want analytics and debugging in one workflow.

2. Segment

Segment (now part of Twilio) is the original CDP and still the most widely adopted. It popularized the idea of a single API for customer data collection, and its tracking spec has become a de facto standard.

Segment's core strength is data routing: install one SDK, define your events, and Segment handles sending that data to 700+ destinations – analytics tools, ad platforms, CRMs, warehouses, and more. This dramatically simplifies instrumentation and makes it easy to add or remove tools without rewriting tracking code.

On the analytics side, the platform now includes Unify for identity resolution and profile building, Twilio Engage for audience activation and journey orchestration, and native integrations with analytics tools like Amplitude and Mixpanel. That being said, Segment still doesn't include built-in product analytics, funnels, or session replay – you'll need to pair it with another tool for that.

Pricing is based on Monthly Tracked Users (MTUs). There's a free tier with 1,000 MTUs and 500K/mo Reverse ETL Records, a Team plan starting at $120/month for 10,000 MTUs and 1M/mo Reverse ETL Records, and custom Business pricing for larger deployments. CDP features (Unify, Engage) require custom pricing.

Strengths:

• Industry-standard tracking spec with excellent documentation
• 700+ pre-built integrations
• Strong identity resolution with Unify
• Reliable, battle-tested infrastructure at scale
• Deep Twilio ecosystem integration (SMS, email, voice)

Community:

• SDKs are open source on GitHub
• Large ecosystem of agencies and consultants
• Active community forum

Segment is best for...

Teams that want a best-in-class data pipeline, comfortable pairing it with separate analytics and BI tools, and willing to pay for a premium, fully managed solution.

3. RudderStack

RudderStack is an open-source CDP built specifically for developers and data teams. It positions itself as a warehouse-native alternative to Segment, designed for teams that want their data warehouse (Snowflake, BigQuery, Redshift) to be the source of truth – not a vendor's platform.

RudderStack's architecture is different from traditional CDPs: instead of storing customer data in its own database, it routes data directly to your warehouse and lets you build identity resolution, audiences, and activation on top of your existing infrastructure. This means no data duplication, better governance, and lower vendor lock-in.

The platform includes event streaming (similar to Segment), transformations you can write in JavaScript or Python, identity stitching via Profiles, and reverse ETL to sync warehouse data back to tools. There's also a visual audience builder, though it's more limited than enterprise CDP offerings.

RudderStack offers a free tier for up to 250,000 events/month, with paid plans starting at $220/month for the Starter tier with 1M events/mo. Enterprise pricing is custom.

Strengths:

• Warehouse-native architecture – your data stays in your warehouse
• Developer-friendly with Git-based workflows and custom transformations
• Strong Segment compatibility (forked tracking specs)
• 200+ integrations including warehouses, streaming platforms, and tools
• Open source and self-hostable

Community:

• Open source on GitHub
• 4.3k+ stars, 100+ contributors
• Active community Slack

RudderStack is best for...

Data-savvy engineering teams who want a Segment alternative that keeps data in their warehouse, supports custom transformations, and doesn't create another data silo.

4. mParticle

mParticle is an enterprise CDP focused on real-time data orchestration, particularly for mobile-first companies. It's used by brands like HBO Max, JetBlue, and Marks & Spencer to unify customer data across apps, web, and backend systems.

mParticle's core differentiator is its real-time processing engine: data flows through in milliseconds, enabling immediate personalization, suppression, and audience activation. The platform also has strong mobile SDK support, which makes it popular with app-heavy businesses.

On the analytics side, mParticle includes built-in data quality monitoring, identity analytics, and an AI-powered audience builder that can create predictive segments (likelihood to purchase, churn risk). However, like Segment, it doesn't include product analytics – you'll typically pair it with a standalone analytics or BI tool.

mParticle uses credit-based pricing aimed at enterprise teams. Customers commit to an upfront pool of credits, which are then consumed based on usage of each feature. All features are included by default, with no per-feature tiers or hard caps. Rates vary based on the size of commitment, meaning costs scale with data volume but require working with sales to estimate and manage spend.

Strengths:

• Real-time data processing with sub-second latency
• Strong mobile SDK support
• AI-powered predictive audiences
• Robust data quality and governance tools
• Hundreds of integrations including major ad and marketing platforms

Community:

• Closed-source platform
• Active partner ecosystem
• Regular product updates via their blog

mParticle is best for...

Mobile-first companies and large organizations that need robust identity management and audience orchestration at scale.

5. Hightouch

Hightouch pioneered the "composable CDP" – a fundamentally different architecture where your data warehouse is the CDP. Instead of collecting and storing data in a separate platform, Hightouch sits on top of Snowflake, BigQuery, Databricks, or Redshift and activates the data that's already there.

This approach has major advantages: no data duplication, no new data silos, full SQL access, and you can leverage all the modeling and transformation work your data team has already done. Hightouch syncs audiences, user attributes, and computed fields from your warehouse to 250+ destinations in real-time or on a schedule.

Hightouch has expanded beyond reverse ETL into a full composable CDP with Customer Studio (no-code audience builder), identity resolution, journey orchestration, and AI-powered decisioning. The platform is designed to give marketers self-service access to warehouse data without requiring SQL knowledge.

The free tier includes basic reverse ETL functionality. Paid plans (Composable CDP, AI Decisioning) are custom-priced based on usage.

Strengths:

• Warehouse-native – no data duplication or vendor lock-in
• Leverages existing data infrastructure and models
• No-code audience builder for non-technical users
• 250+ integrations
• Fast implementation (days/weeks, not months)

Community:

• Closed-source platform
• Backed by Snowflake and Databricks (strategic investors)

Hightouch is best for...

Data teams with mature warehouse infrastructure who want to activate existing data without building another silo – especially if marketers need self-service audience access.

6. Tealium

Tealium is an enterprise CDP that grew out of tag management – and that heritage shows in its comprehensive data collection and integration capabilities.

Their Customer Data Hub consists of several products that work together delivering client-side data collection, server-side API data, identity resolution and audience activation, and machine learning-powered insights like churn prediction and purchase propensity.

The platform's standout feature is its integration library: 1,300+ pre-built connectors to marketing, analytics, and data tools. Tealium also has strong real-time capabilities with patented "visitor stitching" technology for identity resolution, and robust privacy/compliance features (HIPAA, ISO 27001, SOC 2).

Tealium doesn't include built-in product analytics, funnels, or session replay – you'll pair it with external analytics tools.

Pricing is based on events collected and is custom-quoted.

Strengths:

• 1,300+ pre-built integrations – largest in the CDP market
• Strong tag management heritage with both client-side and server-side collection
• Real-time identity resolution with patented visitor stitching
• Robust privacy and compliance certifications (HIPAA, ISO 27001, SOC 2)
• ML-powered predictive insights with Predict ML add-on
• CloudStream for warehouse-native activation without data duplication

Community:

• Closed-source platform
• Strong partner and consultant ecosystem

Tealium is best for...

Mid-to-large enterprise teams with complex martech stacks who need comprehensive data collection, strong compliance features, and the largest integration library in the market.

• Want a CDP with built-in analytics features? PostHog.
• Want an industry-standard data layer with 700+ integrations? Segment.
• Want an open-source, warehouse-native alternative to Segment? RudderStack.
• Need real-time data orchestration for a mobile-first app? mParticle.
• Already have a data warehouse and want to activate it without building a new silo? Hightouch.
• Need the largest integration library and enterprise-grade compliance? Tealium.

For startups and small teams

• PostHog if you want everything in one place – analytics, replay, flags, error tracking, and data pipelines – without managing multiple vendors
• Segment (free tier) if you're building a data layer and want maximum flexibility in tool choice

For developer-first teams

• PostHog for teams that SDKs in all their favorite languages, customizable destinations and transformations, and docs that make all this easy to self-serve
• RudderStack for teams that want a warehouse-native CDP with full control over transformations and routing

For teams with their own warehouses

• Segment if you have budget and want a mature, well-supported platform with broad integrations
• Hightouch if your data team has already invested in a warehouse and wants to activate that data

For enterprises

• Tealium for complex martech stacks, 1,300+ integrations, and strong compliance (HIPAA, ISO 27001)
• mParticle for real-time orchestration, strong governance, and enterprise support
• Segment (Business tier) for teams already in the Twilio ecosystem
• PostHog if you want an all-in-one platform with strong governance and raw data access

For warehouse-first teams

• Hightouch if you want to activate existing warehouse data without building a new silo
• RudderStack if you also need event collection and want open-source infrastructure

Is PostHog right for you?

Here's the (short) sales pitch.

We're biased, obviously, but PostHog is the best choice for a CDP if:

• You want data pipelines connected to analytics, session replay, feature flags, and more – all in one platform instead of stitching tools together
• You value open source and transparent pricing
• You want to try before you buy with 1 million events and 10K dispatches free every month

It's completely free to get started – no credit card required. Our setup wizard handles configuration in minutes, or you can check out our docs to do it yourself.

What is a CDP, actually?

A Customer Data Platform (CDP) is software that collects customer data from multiple sources, creates unified customer profiles through identity resolution, and makes that data available for analysis and activation in other tools.

The key difference from a CRM or data warehouse is that CDPs specialize in unifying customer identities across touchpoints and activating that data in real-time across marketing, sales, and product tools.

Do I need a CDP if I have a data warehouse?

Not necessarily. If your warehouse is already your source of truth and your team is comfortable modeling data and building pipelines, you may not need a traditional CDP.

A CDP is most useful earlier in the data flow: it simplifies capturing events from apps and services, standardizing them, and reliably piping that data into your warehouse. Some CDPs also help move modeled data back out to other tools (often called reverse ETL), but many teams handle this with dedicated data pipeline tools like Fivetran or with native warehouse connectors.

In practice, a CDP reduces the amount of custom ingestion and plumbing you need to build. Whether that's worth it depends on how much instrumentation and data movement you want to manage yourself versus outsourcing to a platform.

What's the difference between a CDP and a data warehouse?

A data warehouse (Snowflake, BigQuery, Redshift) is a general-purpose storage and compute layer for structured data. It can hold customer data, but it doesn't specialize in identity resolution or real-time activation.

A CDP is purpose-built for customer data: it collects from multiple sources, resolves identities, builds profiles, and syncs data to downstream tools. Some CDPs store data themselves; "composable CDPs" like Hightouch sit on top of your warehouse instead.

Tools like PostHog blur the line by including both a data warehouse and CDP capabilities in one platform.

If you want to go deeper on how CDPs fit into a modern data stack, check out our guide on CDP vs data warehouse: which should you use and why.

What's identity resolution and why does it matter?

Identity resolution is the process of stitching together data about the same person from different sources and devices. For example, connecting an anonymous website visitor to their email address after signup, then linking that to their mobile app activity.

Good identity resolution means your analytics tools have accurate, complete customer profiles – not fragmented data that treats one person as three different users.

What's the difference between deterministic and probabilistic identity resolution?

Deterministic identity resolution uses known identifiers (email, user ID, phone number) to match records. It's highly accurate but only works when you have those identifiers.

Probabilistic identity resolution uses signals like IP address, device fingerprint, and behavior patterns to infer matches. It can resolve more identities but with lower confidence.

Most developer-focused CDPs use deterministic resolution. Enterprise CDPs often include probabilistic matching for marketing use cases.

What's a "composable CDP"?

A composable CDP is a CDP architecture where your data warehouse serves as the storage layer instead of the CDP vendor's platform. Tools like Hightouch and Census sit on top of your warehouse and provide identity resolution, audience building, and syncing – without duplicating your data.

The benefit is less vendor lock-in and better data governance. The tradeoff is you need a mature data warehouse setup first.

How do CDPs handle privacy and consent?

CDPs vary widely in their privacy features. Most support consent management integrations and can filter data based on user preferences. Some (like Segment and mParticle) include built-in consent enforcement; others rely on upstream tools.

For GDPR/CCPA compliance, look for: consent-based data collection, easy data deletion (right to erasure), and controls over which downstream tools receive PII.

What should I look for in CDP pricing?

CDP pricing typically scales with:

• Monthly Tracked Users (MTUs): unique users identified per month
• Events: number of data points ingested
• Destinations: number of tools you sync data to
• Features: identity resolution, audiences, and activation often cost extra

Watch for: low free tiers that force early upgrades, steep MTU-based scaling, and feature-gated pricing where core CDP functionality requires enterprise plans.

Can I use a CDP without being a large enterprise?

Yes. Tools like PostHog, Segment, and RudderStack have generous free tiers that work well for startups.

If you're small, you might get more value from an all-in-one tool (like PostHog) that includes analytics and data routing, rather than paying for a standalone CDP and separate analytics platform.

Do CDPs include product analytics?

Most traditional CDPs (Segment, mParticle, Hightouch) do not include product analytics. They're designed to collect and route data to analytics tools, not replace them.

PostHog is an exception, and a good example of a CDP with analytics features: it includes full product analytics, session replay, feature flags, and experiments alongside CDP functionality – so you can analyze data without exporting it to another tool.

Which CDP is best for developers?

PostHog and RudderStack are the most developer-friendly options. Both are open source (or have open-source cores), offer SQL access, and support custom transformations.

Segment is well-documented and has excellent SDKs, but the platform itself is closed-source and enterprise-priced.

Which CDP is best for app developers, specifically?

For mobile-first teams, mParticle is purpose-built for apps with strong iOS and Android SDKs, real-time event streaming, and deep integrations with mobile attribution and marketing tools.

For product-led apps where you want analytics, experimentation, and data routing in one platform, PostHog offers native mobile SDKs (iOS, Android, React Native, Flutter) alongside product analytics, session replay, and feature flags – so you can understand user behavior and ship improvements without stitching together multiple tools.

Segment is also a solid choice if you need a broad integration library and plan to pair it with separate analytics tools.

Can I self-host a CDP?

Yes. RudderStack offers self-hosted options with complete data ownership. This is useful for teams with strict compliance requirements, data residency needs, or who want to avoid vendor lock-in.

The tradeoff is operational complexity – you'll need to maintain the infrastructure yourself.

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