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Rakam VS Cloudberry Database

Compare Rakam VS Cloudberry Database and see what are their differences

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Rakam logo Rakam

Custom analytics platform

Cloudberry Database logo Cloudberry Database

Next-gen unified database for Analytics and AI.
  • Rakam Landing page
    Landing page //
    2022-01-21
  • Cloudberry Database Landing page
    Landing page //
    2024-05-17

Cloudberry Database is created by a team of original Greenplum Database developers and ASF committers. We aim to bring modern computing capabilities to the traditional distributed MPP database to support Analytics and AI/ML workloads in one platform.

As a derivative of Greenplum Database 7, Cloudberry Database is compatible with Greenplum Database, but it's shipped with a newer PostgreSQL 14.4 kernel (scheduled kernel upgrade yearly) and a bunch of features Greenplum Database lacks or does not support.

Rakam features and specs

  • Customizability
    Rakam allows for extensive customization of analytics and dashboards, making it adaptable to a wide range of use cases and industries.
  • Scalability
    The platform can handle large volumes of data, making it suitable for enterprises as well as growing startups.
  • Real-time Analysis
    Rakam supports real-time data analytics, enabling businesses to make informed decisions quickly based on the latest data.
  • Integration
    It integrates well with other data sources and tools, allowing users to create a cohesive analytics ecosystem.
  • User-friendly Interface
    The platform provides an intuitive and easy-to-use interface, which helps users with varying levels of technical expertise to navigate and utilize its features effectively.

Possible disadvantages of Rakam

  • Cost
    For small businesses or startups with limited budgets, the cost of using Rakam might be a significant consideration.
  • Learning Curve
    While the interface is user-friendly, the extensive customization options available may require a time investment to fully understand and utilize.
  • Limited Pre-built Templates
    Rakam has fewer pre-built templates compared to some other analytics platforms, potentially requiring more initial setup time for new users.
  • Customer Support
    Some users have reported that customer support response times and the level of available assistance can be inconsistent.
  • Complexity for Basic Users
    The platform's advanced features and customization options might be overwhelming for users looking for basic analytics solutions.

Cloudberry Database features and specs

  • Scalability
    Cloudberry Database is designed to handle large datasets and can scale efficiently across distributed systems, making it suitable for big data applications.
  • Real-Time Data Processing
    The database supports real-time data analytics, which is beneficial for applications that require immediate insights from data as it arrives.
  • Integration with Apache Ecosystem
    As part of the Apache ecosystem, Cloudberry Database integrates well with other Apache projects, enhancing its functionality and ease of use for users already leveraging Apache tools.
  • Open Source
    Being an open-source database, Cloudberry allows users to customize and extend the database functionalities according to their specific needs without incurring additional costs.

Possible disadvantages of Cloudberry Database

  • Complex Setup
    Setting up and configuring Cloudberry Database can be complex, requiring specialized knowledge and expertise, which may not be suitable for all organizations.
  • Limited Community Support
    Compared to more established databases, Cloudberry might have a smaller user community, potentially resulting in limited support and resources.
  • Performance Overhead
    While powerful, the system might introduce additional performance overhead due to its distributed nature, potentially affecting latency in some cases.
  • Less Mature
    As a newer technology, Cloudberry might not have the same level of maturity and stability as older, more established databases.

Analysis of Rakam

Overall verdict

  • Rakam is a good solution for companies looking for an efficient and scalable analytics platform. It offers a range of features that can meet the needs of small to large enterprises, providing valuable insights through its customizable dashboards and reports.

Why this product is good

  • Rakam is a comprehensive analytics platform that offers powerful features for data analysis, business intelligence, and custom reporting. It provides a flexible and scalable infrastructure that allows businesses to collect and analyze data in real-time, helping them make informed decisions. The platform is designed to be user-friendly with support for different data sources, making it suitable for teams without extensive technical expertise.

Recommended for

    Rakam is particularly recommended for startups, small to medium-sized businesses, and any organization that requires a robust yet easy-to-use analytics platform. It is also suitable for teams that need to integrate multiple data sources and are looking for an alternative to more complex or expensive analytics solutions.

Analysis of Cloudberry Database

Overall verdict

  • Apache Cloudberry is a promising open-source, PostgreSQL-compatible massively parallel processing (MPP) database derived from Greenplum, offering solid analytical performance and enterprise-grade features under a permissive Apache 2.0 license, making it a good choice for organizations seeking a vendor-neutral, community-driven alternative to proprietary MPP databases—though as a newer Apache incubator project, it still lacks the maturity, ecosystem breadth, and long-term track record of more established data warehouse solutions.

Why this product is good

  • Built on PostgreSQL, ensuring strong SQL compatibility and access to the broader PostgreSQL tooling ecosystem
  • MPP architecture enables efficient parallel query processing for large-scale analytical workloads
  • Apache 2.0 licensing removes vendor lock-in and licensing costs associated with proprietary alternatives like Greenplum
  • Backed by the Apache Software Foundation, providing governance, transparency, and community-driven development
  • Inherits mature features from Greenplum lineage, including support for complex analytics, partitioning, and columnar storage
  • Active open-source community allows for transparent development and faster incorporation of community feedback
  • Supports standard PostgreSQL extensions and drivers, easing migration for existing PostgreSQL users

Recommended for

  • Organizations running large-scale analytical and data warehousing workloads who want an open-source alternative to commercial MPP databases
  • Teams already invested in PostgreSQL looking to scale to distributed, parallel processing without changing their SQL dialect
  • Companies wanting to avoid vendor lock-in from proprietary data warehouse solutions
  • Enterprises seeking a Greenplum-compatible platform after Greenplum's commercial licensing changes
  • Technical teams comfortable with early-stage or incubating open-source projects and willing to contribute to or engage with the community
  • Use cases involving heavy analytical queries, BI reporting, and batch data processing rather than high-throughput OLTP transactions

Rakam videos

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Cloudberry Database videos

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Category Popularity

0-100% (relative to Rakam and Cloudberry Database)

Rakam

Cloudberry Database

Big Data Analytics
95 95%
Big Data Analytics
5% 5
Databases
0 0%
Databases
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Database Tools
100 100%
Database Tools
0% 0

User comments

Share your experience with using Rakam and Cloudberry Database. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Cloudberry Database should be more popular than Rakam. It has been mentiond 3 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.

Rakam mentions (1)

  • Show HN: Lightdash – An open source Looker alternative
    Well done! I was actually looking for an open source LookML a while back and found Rakam[0]. It seems they added the dbt layer after the fact while you started with that concept. Product looks slick, good luck? By the way, what happened with Hubble? 0 - https://rakam.io/. - Source: Hacker News / over 5 years ago

Cloudberry Database mentions (3)

  • Migrate the legacy Greenplum to Apache Cloudberry with cbcopy
    ### cbcopy Parameters Reference (Refer to the cbcopy parameter documentation and examples for complete usage and configuration guidance.) ## Welcome to Apache Cloudberry: - **Visit the website:** https://cloudberry.apache.org - **Follow us on GitHub:** https://github.com/apache/cloudberry - **Join Slack workspace:** https://apache-cloudberry.slack.com - **Dev mailing list:** - To subscribe to dev mailing... - Source: dev.to / 9 months ago
  • Distributed Applications. Part 3 - Distributed State
    Leaderful means that all writes have to go through the leader. That prevents scaling, but helps consistency - Postgres being a good example. The way you can achieve scaling with leaders, is by sharding - have portions of data controlled by independent processes, and thus have different leaders. But you sacrifice consistency between shards - and you get Cassandra LightWeight Transactions - docs. They only work... - Source: dev.to / 11 months ago
  • Show HN: Apache Cloudberry 2.0.0 – First ASF release of MPP database
    - Changelog: https://cloudberry.apache.org/releases/2.0.0-incubating. - Source: Hacker News / about 1 year ago

What are some alternatives?

When comparing Rakam and Cloudberry Database, you can also consider the following products

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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

Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

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