5 Reasons why ClickHouse is ‘the’ database for end-user analytics

The world is awash in innovation. The best databases for end-user analytics in 2023 take advantage of vast streams of information in near-real time coupled with terabytes to petabytes of existing information, offering unprecedented speed coupled and extraordinary insights when paired with a modern embeddable visualization tool.

While paid tools exist to accomplish this feat, ClickHouse stands apart in its ability to deliver at minimal cost for even the most demanding applications. As an open-source database, there are no hidden costs or paid upgrades. You have access to everything.

The case for ClickHouseThe case for ClickHouse

BI analytics on massive amounts of data does not need to be an expensive, time-consuming, batch-driven process. ClickHouse’s columnar database architecture and innovative consensus and compression algorithms make it among the best-performing databases for end-user analytics 2023.

Among the many reasons ClickHouse is a potential star on top of your data lake or warehouse are:

• The ability to scale analytics on any volume of real-time or static data

• Production capabilities unparalleled by stream processors and traditional databases

• Simplicity by design and the use of SQL

• Integrations with many popular ingestion and reporting tools

• Low-cost infrastructure

Whether performing predictive and diagnostic analytics or driving a real-time dashboard, ClickHouse has a place in the modern data stack.

1. Scalable Real-Time and Batch Analytics1. 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 ready2. 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 entry3. 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.

4. Extensive integrations4. Extensive integrations

The ease of deployment does not stop with analysts and engineers. ClickHouse is a versatile and scalable solution that easily integrates into a company’s existing data infrastructure from ingestion to visualization.

Support for many popular ingestion and reporting tools, such as Kafka and Hadoop, makes it easy to craft pipelines from existing infrastructure directly in ClickHouse. DoubleCloud brings the entire process online with no need for code.

Beyond the data manipulation layer, it is possible to ingest data through Kafka or a JDBC connector. This brings support for a wide variety of languages along with a significant degree of flexibility. New features allow you to build an entire pipeline from ingestion to push notifications directly from the database.

As an established tool, your journey from data to visualization is fully supported. Access your database from SuperSet, Grafana, PowerBI, and many other tools. DoubleCloud includes built-in dashboard capabilities alongside your database in a single environment.

Combined with AWS or Google Cloud infrastructure, you can create visualizations on top of your lake house or warehouse architecture without additional engineering effort. Integrate gold tier and processed information directly with streaming data to deliver a powerful impact.

5. Low-cost infrastructure5. Low-cost infrastructure

In its ability to combine multiple sources of information and integrate with a vast array of technologies, ClickHouse is an all-in-one OLAP solution and a way to eliminate a patchwork of custom solutions. This helps control costs while alleviating workloads on developers.

As an open-source and free system, you do not need to worry about licenses and paid upgrades either. DoubleCloud charges a low flat rate starting at under $300 for a 32-gigabyte three-node fully managed database.

DoubleCloud offers an additional layer of power on top of your database. Our managed Clickhouse service lets you turn SQL into dashboards without an additional tool. For the less technically inclined, we also offer a click-and-drag interface.

Why add another database to my tech stack?Why add another database to my tech stack?

It may seem counterintuitive to add yet another database to your tech stack. After all, tech debt and cost are significant problems with companies using 40 to 60 SAAS applications. However, a database can actually eliminate tech debt.

In a real-time setup without a database, you would process streams using a tool such as KSQLDB. Data ends up in your warehouse where it is processed and then pushed to a visualization tool, often with its data storage. Multiple tools move data into your OLAP cube.

Even in a data lake, your data goes through multiple layers of processing where it may need to be combined yet again before being visualized. This can lead to complex and even costly queries. It also risks creating a data swamp.

With a database, you do not need to build additional pipelines. You manage business intelligence and data streams in the same way you manage other database systems. Even data governance becomes a matter of issuing simple data definition commands.

Why is ClickHouse among the best databases for end-user analytics?Why is ClickHouse among the best databases for end-user analytics?

Real-time analytics delivers fast and effective results. With trillions of dollars of benefit, it is likely that your competition already leverages real-time power. As a production ready, easy-to-use system, it is likely they are using ClickHouse

DoubleCloud’s fully managed ClickHouse solution takes care of deployments and lets you build powerful fast visualizations in a few simple clicks. Learn more about how our highly scalable service turns warehouses, lake houses, and streaming data into potent end-user dashboards.