Software Alternatives, Accelerators & Startups

SAP BW VS ClickHouse

Compare SAP BW VS ClickHouse and see what are their differences

This page does not exist

SAP BW logo SAP BW

SAP BW Tutorial - SAP Business Warehouse (BW) integrates data from different sources, transforms and consolidates the data, does data cleansing, and storing of data as well. It a

ClickHouse logo ClickHouse

ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.
  • SAP BW Landing page
    Landing page //
    2023-09-24
  • ClickHouse Landing page
    Landing page //
    2019-06-18

SAP BW features and specs

  • Data Integration
    SAP BW provides robust data integration capabilities, allowing businesses to consolidate data from various sources into a single repository for comprehensive analysis.
  • Performance Optimization
    It offers performance optimization tools and techniques such as aggregates, indexes, and partitions, which help improve query performance and data retrieval times.
  • Scalability
    SAP BW is designed to handle large volumes of data, making it scalable for growing businesses and enterprises with extensive data analysis needs.
  • Comprehensive Reporting
    The system supports complex reporting requirements with a wide range of reporting tools and functionalities, enabling detailed analysis and insights.
  • Integration with SAP Ecosystem
    SAP BW integrates seamlessly with other SAP products, enhancing its functionality and providing a cohesive ERP solution for businesses already using SAP systems.

Possible disadvantages of SAP BW

  • Complexity
    The system can be complex to set up and manage, often requiring specialized knowledge and experience, which can be a barrier for smaller organizations.
  • Cost
    SAP BW can be expensive to implement and maintain, with costs associated with licensing, support, and the need for skilled personnel.
  • Steep Learning Curve
    Users may face a steep learning curve due to the complexity and depth of the system, necessitating training and time to become proficient.
  • Maintenance and Upgrades
    Regular maintenance and updates are required to keep the system running optimally, which can be resource-intensive and time-consuming.
  • Customization Limitations
    While offering extensive functionalities, customization may be limited or require additional resources and time to tailor the system to specific business needs.

ClickHouse features and specs

  • High Performance
    ClickHouse is designed for fast processing of analytical queries, often performing significantly faster than traditional databases due to its columnar storage format and optimized query execution.
  • Scalability
    The system is built to handle extensive datasets by scaling horizontally through distributed cluster configurations, making it suitable for big data applications.
  • Real-time Data Ingestion
    ClickHouse supports real-time data ingestion and can immediately reflect changes in query results, which is valuable for use cases requiring instant data processing and analysis.
  • Cost Efficiency
    The open-source nature of ClickHouse makes it a cost-effective option, especially when compared to other commercial data warehouses.
  • SQL Compatibility
    ClickHouse features strong SQL support, which makes it easier for individuals with SQL expertise to transition and use the platform effectively.
  • Compression
    ClickHouse employs advanced compression algorithms that reduce storage requirements and improve query performance.

Possible disadvantages of ClickHouse

  • Complexity in Setup
    Setting up and managing ClickHouse, particularly in a distributed cluster environment, can be complex and require a higher level of expertise compared to some other database systems.
  • Limited Transaction Support
    ClickHouse is optimized for read-heavy operations and analytics but does not support full ACID transactions, which limits its use for certain transactional use cases.
  • Ecosystem and Tooling
    While the ecosystem is growing, ClickHouse still has fewer tools and third-party integrations compared to more mature databases, which can limit its utility in some environments.
  • Resource Intensive
    Running ClickHouse, especially for large datasets, can be resource-intensive, requiring significant memory and CPU resources.
  • Limited User Management
    The platform has relatively basic user management and security features, which may not meet the needs of enterprises with strict compliance and governance requirements.

Analysis of ClickHouse

Overall verdict

  • ClickHouse is a powerful and capable columnar DBMS that offers excellent performance for analytical workloads. Its open-source nature allows for flexibility and community-driven improvements, making it a strong option for organizations needing a scalable analytics platform.

Why this product is good

  • ClickHouse is considered a good choice for many use cases due to its high performance in processing large volumes of data and its efficiency in executing complex analytical queries. It is designed to work well with large datasets and provides real-time query capabilities, making it ideal for applications like business intelligence, web analytics, and IoT.

Recommended for

  • Large-scale data analysis
  • Real-time analytics dashboards
  • Businesses needing high-speed query performance
  • Web analytics platforms
  • IoT data processing
  • Financial industry for quick data aggregation

SAP BW videos

Sap Bw Training Hq Review

More videos:

  • Review - SAP BW/4HANA Introduction to Beginners | ZaranTech

ClickHouse videos

No ClickHouse videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to SAP BW and ClickHouse)
Databases
9 9%
91% 91
Big Data
32 32%
68% 68
Relational Databases
11 11%
89% 89
Data Warehousing
11 11%
89% 89

User comments

Share your experience with using SAP BW and ClickHouse. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare SAP BW and ClickHouse

SAP BW Reviews

We have no reviews of SAP BW yet.
Be the first one to post

ClickHouse Reviews

Rockset, ClickHouse, Apache Druid, or Apache Pinot? Which is the best database for customer-facing analytics?
โ€ClickHouse is an open-source, column-oriented, distributed, and OLAP database thatโ€™s very easy to set up and maintain. โ€œBecause itโ€™s columnar, itโ€™s the best architectural approach for aggregations and for โ€˜sort byโ€™ on more than one column. It also means that group byโ€™s are very fast. Itโ€™s distributed, replication is asynchronous, and itโ€™s OLAPโ€”which means itโ€™s meant for...
Source: embeddable.com
ClickHouse vs TimescaleDB
Recently, TimescaleDB published a blog comparing ClickHouse & TimescaleDB using timescale/tsbs, a timeseries benchmarking framework. I have some experience with PostgreSQL and ClickHouse but never got the chance to play with TimescaleDB. Some of the claims about TimescaleDB made in their post are very bold, that made me even more curious. I thought itโ€™d be a great...
20+ MongoDB Alternatives You Should Know About
ClickHouse may be a great contender for moving analytical workloads from MongoDB. Much faster, and with JSON support and Nested Data Structures, it can be great choice for storing and analyzing document data.
Source: www.percona.com

Social recommendations and mentions

Based on our record, ClickHouse seems to be more popular. It has been mentiond 60 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

SAP BW mentions (0)

We have not tracked any mentions of SAP BW yet. Tracking of SAP BW recommendations started around Mar 2021.

ClickHouse mentions (60)

  • Setting up ClickHouse on macOS and Testing with Node.js
    ClickHouse is an open-source columnar database built for high-performance analytical queries. This guide shows how I installed ClickHouse on macOS, ran it in the background using a lightweight nohup setup that stores logs and PID in hidden user folders, and tested it with a minimal Node.js + TypeScript example using @clickhouse/client. - Source: dev.to / 15 days ago
  • From Go to Rust: Supercharging Our ClickHouse UDFs with Alloy
    At Agnostic, we build open-source infrastructure for collaborative blockchain data platforms. One of our flagship tools is clickhouse-evm, a suite of high-performance User Defined Functions (UDFs) that brings native Ethereum decoding and querying capabilities directly into ClickHouse. - Source: dev.to / 3 months ago
  • ๐Ÿง  From Hive and Elastic to ClickHouse: What Surprised Me
    Over the past few weeks, Iโ€™ve been diving into ClickHouse โ€” and itโ€™s been full of surprises. - Source: dev.to / 3 months ago
  • Cross-Compiling Haskell under NixOS with Docker
    I attended the AWS Summit 2025 in Singapore. I enjoyed the event. There were booths from various companies which I found interesting, such as GitLab and ClickHouse. More importantly, I got to meet very interesting people. - Source: dev.to / 4 months ago
  • How to Build a Streaming Deduplication Pipeline with Kafka, GlassFlow, and ClickHouse
    ClickHouse: A fast columnar database. It will be our final destination for clean data. And, for simplicity in this tutorial, we'll cleverly use it as our "memory" or state store to remember which events we've already seen recently. - Source: dev.to / 5 months ago
View more

What are some alternatives?

When comparing SAP BW and ClickHouse, you can also consider the following products

Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.

MySQL - The world's most popular open source database

Greenplum Database - Greenplum Database is an open source parallel data warehousing platform.

Apache Doris - Apache Doris is an open-source real-time data warehouse for big data analytics.

Teradata Database - Teradata Database is a high performance analytical database.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.