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Census

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Google BigQuery

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Google BigQuery vs Census: What are the differences?

Developers describe Google BigQuery as "Analyze terabytes of data in seconds". Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.. On the other hand, Census is detailed as "Sync your warehouse data to any app". 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.

Google BigQuery and Census can be categorized as "Big Data as a Service" tools.

Some of the features offered by Google BigQuery are:

  • All behind the scenes- Your queries can execute asynchronously in the background, and can be polled for status.
  • Import data with ease- Bulk load your data using Google Cloud Storage or stream it in bursts of up to 1,000 rows per second.
  • Affordable big data- The first Terabyte of data processed each month is free.

On the other hand, Census provides the following key features:

  • Turn your warehouse into a Customer Data Platform
  • Sync with customer facing tools
  • No more data outages
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Pros of Census
Pros of Google BigQuery
    Be the first to leave a pro
    • 28
      High Performance
    • 25
      Easy to use
    • 22
      Fully managed service
    • 19
      Cheap Pricing
    • 16
      Process hundreds of GB in seconds
    • 12
      Big Data
    • 11
      Full table scans in seconds, no indexes needed
    • 8
      Always on, no per-hour costs
    • 6
      Good combination with fluentd
    • 4
      Machine learning
    • 1
      Easy to manage
    • 0
      Easy to learn

    Sign up to add or upvote prosMake informed product decisions

    Cons of Census
    Cons of Google BigQuery
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      • 1
        You can't unit test changes in BQ data
      • 0
        Sdas

      Sign up to add or upvote consMake informed product decisions

      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 Google BigQuery?

      Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

      Need advice about which tool to choose?Ask the StackShare community!

      Jobs that mention Census and Google BigQuery as a desired skillset
      What companies use Census?
      What companies use Google BigQuery?
      Manage your open source components, licenses, and vulnerabilities
      Learn More

      Sign up to get full access to all the companiesMake informed product decisions

      What tools integrate with Census?
      What tools integrate with Google BigQuery?

      Sign up to get full access to all the tool integrationsMake informed product decisions

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      What are some alternatives to Census and Google BigQuery?
      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