Nov 3, 2018

Advantages of Google Cloud Bigtable

Google Cloud Bigtable

Cloud Bigtable is a sparsely populated table that can scale to billions of rows and thousands of columns, allowing you to store terabytes or even petabytes of data. A single value in each row is indexed; this value is known as the row key. Cloud Bigtable is ideal for storing very large amounts of single-keyed data with very low latency. It supports high read and write throughput at low latency, and it is an ideal data source for MapReduce operations.
Cloud Bigtable is exposed to applications through multiple clients, including a supported extension to the Apache HBase 1.x Java library. As a result, it integrates with the existing Apache ecosystem of open-source Big Data software.
Cloud Bigtable's powerful back-end servers offer several key advantages over a self-managed HBase installation:
  • Incredible scalability. Cloud Bigtable scales in direct proportion to the number of machines in your cluster. A self-managed HBase installation has a design bottleneck that limits the performance after a certain QPS is reached. Cloud Bigtable does not have this bottleneck, and so you can scale your instance up to handle more queries by increasing your machine count.
  • Simple administration. Cloud Bigtable handles replication, upgrades, and restarts transparently. No more managing masters, regions, clusters, or nodes; all this is done automatically. All you need to do is design your table schemas, and Cloud Bigtable will handle the rest for you.
  • Cluster resizing without downtime. You can increase the size of your Cloud Bigtable cluster for a few hours to handle a large load, then reduce the cluster's size again—all without any downtime. After you change a cluster's size, it typically takes just a few minutes under load for Cloud Bigtable to balance performance across all of the nodes in your cluster.