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Census vs Fivetran: What are the differences?

Introduction:

In the realm of data management and analytics, both Census and Fivetran hold significance, but there exist key differences between the two platforms. This Markdown document highlights and explains those disparities in a concise manner.

  1. Data Collection and Integration: Census is primarily a data collection platform that focuses on tracking user behavioral data and consolidating it from various sources to create a centralized customer data warehouse. On the other hand, Fivetran specializes in automated data integration, pulling data from different sources (including databases, APIs, and file systems) and loading it into a centralized location for analysis.

  2. Automation Approach: While Census allows for automation to some extent, it primarily relies on a no-code workflow builder to create custom data workflows and pipelines. In contrast, Fivetran's automation capabilities are much more robust, providing fully automated data pipeline setup, maintenance, and schema migrations, thus reducing manual configuration and development efforts.

  3. Real-time Data Syncing: Census places a strong emphasis on real-time data syncing, allowing users to track and respond to real-time events or changes. Its infrastructure enables capturing and syncing user data from different platforms in near real-time. Conversely, Fivetran typically syncs data on a scheduled basis, offering data freshness ranging from a few minutes to a few hours.

  4. Data Transformation Abilities: One significant distinction between Census and Fivetran lies in their approaches to data transformation. Census allows users to perform complex transformations within its platform, empowering analysts with the ability to clean, manipulate, and enrich data before feeding it into their data warehouse. In contrast, Fivetran's primary focus is on the extraction and loading of data without offering built-in data transformation capabilities, requiring users to rely on downstream tools for such operations.

  5. Data Warehousing: Census provides a cloud-based data warehouse solution called Census Warehouse, allowing users to store and analyze their consolidated data within the platform itself. Meanwhile, Fivetran does not offer a native data warehousing solution but integrates seamlessly with popular data warehouses such as Snowflake, Redshift, and BigQuery, enabling users to choose their preferred data storage and analysis platforms.

  6. Pricing Model: Census employs a usage-based pricing model, billing customers based on factors such as monthly tracked users and data volume processed. Fivetran, on the other hand, follows a subscription-based pricing approach, offering different pricing tiers based on factors like the number of data connectors, data rows, and data sources required.

In summary, Census primarily focuses on data collection, real-time syncing, and data transformations within its platform, while Fivetran specializes in automated data integration, synchronization, and storage in third-party data warehouses.

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What is Census?

It syncs your data warehouse with CRM & go-to-market tools. Get your customer success, sales & marketing teams on the same page by sharing the same customer data.

What is Fivetran?

It helps you centralize data from disparate sources which you can manage directly from your browser. We extract your data and load it into your data destination.

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What are some alternatives to Census and Fivetran?
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
See all alternatives