Big Data

Large, varied information sets that are expanding at an exponential rate are referred to as big data. It is used to describe high-volume, high-velocity, and/or high-variety information assets that call for creative, cost-effective methods of information processing to improve insight, decision-making, and process automation.

Clickhouse
Clickhouse

A column-oriented database designed for online analytical data processing. Clickhouse can easily manage billions of data points in a single table due to data compression, storing values in sorted files, and a query engine that is designed to deal with calculating aggregations.

ClickHouse offers an extended SQL-like language for querying the data.

Clickhouse features:

  • Clickhouse is a True Column-Oriented DBMS.A column-oriented DBMS or columnar DBMS is a database management system (DBMS) that stores data tables by column rather than by row.
  • LZ4 and ZSTD are the two compression techniques that ClickHouse suggests, allowing you to select the one that best suits your situation, hardware configuration, and workload. Where I/O is the bottleneck in queries with large range scans, zstd is preferred. When I/O is fast enough that decompression speed becomes a bottleneck, LZ4 is preferred.
  • It is feasible to extract data for its specific values or value ranges with low latency, less than a few dozen milliseconds, by maintaining data physically sorted by primary key.
  • In order to achieve great CPU efficiency, data is not only stored by columns but is also processed by vectors (pieces of columns).
  • Primary key-enabled tables are supported by ClickHouse. The data is incrementally sorted using the merge tree to provide rapid queries on the range of the primary key. This allows the table to continuously add new data. New data is consumed without any locks being taken.
  • Asynchronous multi-master replication is used by ClickHouse. All the remaining replicas retrieve their copy in the background after being written to any accessible replica. The system keeps the same data on various clones. Most failures are recovered from automatically or partially in complex scenarios.
  • Using SQL queries, ClickHouse implements user account management and enables role-based access control setup that is comparable to that found in relational database management systems and the ANSI SQL standard.
  • Parallel Processing on Multiple Cores
  • Distributed Processing on Multiple Servers
  • SQL Support

IOTASCALE has the required capabilities and have already developed multiple solutions and products handling billion of rows per day.