Cloud Bigtable powers major Google products like Search and Maps. You can use this incredibly scalable database for analyzing large workloads, such as your customers’ purchase histories and preferences, or currency exchange rates. Bigtable is cheap, scalable, fast, and reliable. This article outlines Bigtable’s attributes, uses, strengths, and weaknesses so you can evaluate whether it’s the right tool for you in any context.
What is Bigtable?
Bigtable is Google Cloud’s fully-managed, NoSQL database for large analytical and operational workloads. This innovative database:
Supports high read/write speed per second.
Processes these reads/writes at ultra-low latency, on the order of single-digit microseconds.
Scales to billions of rows and thousands of columns, adapting itself to terabytes, if not petabytes, of data.
Bigtable is ideal for Cloud data visualization products, such as BigQuery, DataFlow, and DataProc. You can use Cloud Bigtable in various ways, such as for storing marketing data, financial data, and Internet of Things data (e.g., usage reports from energy meters and home appliances). You can also use it for storing time-series data (e.g., CPU usage over time for multiple servers) and graph data (e.g., hospital patients’ dosage regimen over a period of years).
What does Bigtable bring to the table?
Bigtable is a dynamic product with many identifiable assets. The following are the three that most set it apart from the other products in its field:
Speed: The database processes quantities of reads/ writes on the order of 10,000 rows per second.
Scalability: You can stretch that table by adding or removing nodes. Each node - or compute resource that Bigtable uses to manage your data - gives you additional storage capacity.
Reliability: Bigtable gives you key-level performance, stability, and tools for debugging that usually takes far longer on a self-hosted data store.
How does Bigtable work?
Cloud Bigtable is superbly simple. The following four functions will alow you to execute almost any project you’re using Bigtable to support:
Scale or descale the Table by adding or removing nodes.
Replicate your data by adding clusters; replication starts automatically. Clusters describe where your data is stored and how many nodes are used for your data.
Group columns that relate to each other into “column families” for organizational purposes.
Incorporate time stamps by creating rows for each new event or measurement instead of adding cells in existing rows. (This makes Bigtable great for time series analysis).
Bigtable integrates well with Big Data tools such as Hadoop, DataFlow, Beam, and Apache HBase, making it a cinch for users to get started.
Some of the world’s most recognizable companies and institutions have used Bigtable for projects managing massive amounts of data. A small but representative sample of these projects follows below.
Dow Jones, one of the world’s largest news organizations, used Bigtable to structure its Knowledge Graph. The tool compressed key global events from 1.3 billion documents over a 30-year period into Bigtable, for users to mine for insights. Users could also customize the Graph to suit their needs. “With the help of Cloud Bigtable,” a spokesperson from Dow Jones partner Quantiphi said, “we can easily store a huge corpus of data that needs to be processed, and BigQuery allows data manipulations in split seconds, helping to curate the data very easily.”
Ravelin, a digital fraud detection and payment solution company for online retailers, uses Bigtable to effortlessly and seamlessly store and query over 1.2 billion transactions of the clients of its more than 230 million active users. Ravelin also profits from Bigtable’s encrypted security mechanisms. According to Jono MacDougall, Principal Software Engineer at Ravelin: “We like Cloud Bigtable because it can quickly and securely ingest and process a high volume of data.”
AdTech provider OpenX serves more than 30,000 brands, more than 1,200 websites, and more than 2,000 premium mobile apps. It also processes more than 150 billion ad requests per day and about 1 million such requests per second, so it needed a highly scalable, extremely fast, fully managed database to fit its needs. Bigtable provided the perfect solution.
How do I know if Bigtable is right for me?
As powerful as Bigtable is, it’s not a good choice for every situation. In certain contexts, you’ll want to keep other options in mind. For example:
Choose SQL-structured Spanner if you need ultra-strong consistency.
Use NoSQL Cloud Firestore if you want a flexible data model with strong consistency.
Opt for SQL-based BigQuery if you need an enterprise data warehouse that gives you insights into your massive amounts of business data.
Ready to set up Bigtable?
You can create a Bigtable instance using Cloud Console’s the project selector page, or the Cloud Bigtable Admin API. However, Bigtable isn’t free. Users pay by type of instance and amount of nodes, how much storage a table uses, and how much bandwidth Bigtable uses overall. (Here’s all you need to know on Bigtable pricing across countries).
Next time you’re looking to analyze large workloads, take a minute to check out Bigtable. It could help you crunch all that information in a matter of minutes.
Have you ever used Bigtable? For what kinds of projects? How did it work for you? Start a conversation in one of our community groups and share your story!