1. Scalable Real-Time and Batch Analytics
The world is in transition. Eighty percent of businesses now see real-time analytics as critical to driving revenue. At the same time, more static datasets are reaching the petabyte scale and beyond while the demand to couple both types of data is at an all-time high.
Organizations seek to speed up their time to insight for a good reason. They saved a combined total of $321 billion while increasing revenue by $2.6 trillion with real-time analytics platforms alone by 2022.
This hybrid model is not relegated to the realms of business and financial analytics. Retail stores want to capitalize on the success of marketing campaigns. Casinos want to offer bonuses that maximize revenue. Healthcare organizations need to spot problems as they occur.
The need for real-time analysis is diverse. Waiting hours for reports is simply not an option when seeking to make the most of your data. Gaining a competitive edge in today’s fast-paced business landscape requires more than intuition and attention to detail during peak hours.
ClickHouse takes an entirely different approach to storing and accessing data than both relational OLTP and analytical OLAP databases, enabling this new world of discovery. You can scale your cluster to 10,000 tables across hundreds of nodes while processing hundreds of millions of rows per second.
The use of the RAFT algorithm eliminates locks even when inserting millions of rows. Build and maintain extensive dashboards without worrying about the lock conflicts that define RDBMS-based systems, even massively parallel architectures.
2. Production ready
ClickHouse, while capable, is not alone at promising speed. Many solutions offer fast and powerful analytics in batch, real, or near-real time.
Stream processors such as KSQLDB or Windmill promise instant availability. Redshift now tries to optimize databases with automatically built materialized views alongside the ability to ingest data from Kafka.
Unfortunately, many of these solutions lack the core features required by production environments. For instance, persistence and the flexibility to answer any question are major roadblocks in today’s popular streaming tools.
Stream processors do not offer any form of persistence. They lack durability entirely. Messages not stored elsewhere are lost if the service crashes, forcing reliance on complex and slower data lakes, relational warehouses, or file systems to ensure all data is present.
Redshift requires batch processing to make use of streaming data beyond an initial materialized view. There are no triggers, requiring an orchestration tool for batch and real-time datasets.
ClickHouse mixes stream processing and storage both in memory and on disk to help analysts explore data safely and at speed. The risk of losing data is much lower while it is possible to join and aggregate disparate forms of information through the use of specialized table-based processing engines.
DoubleCloud, through fully managed services, offers an additional layer of protection as well. We help you scale safely and automatically using best practices when setting up databases on EC2 instances or within the Google Cloud Platform.
3. Low barrier to entry
Another major problem plagues today’s popular data systems. Companies want to hit the ground running with minimal training. However, stream processing is complex by nature. Tools and languages require multiple paths and layers before data is accessed.
DoubleCloud’s simple user interface for SQL offers unparalleled comfort and familiarity for data analysts, engineers, and developers alike. There is no need to learn additional languages or navigate complicated interfaces.
While data engineers may choose to process data before storing it in DoubleCloud, everything else can be done in SQL. Nearly 100 percent of data engineers and 65 percent of analysts use SQL.
Window functions, aggregates, and joins are all at the fingertips of engineers and analysts, including on streams. Double Cloud’s managed database makes the process even easier by placing real-time analytics a few clicks away, complete with out-of-the-box migration tools.