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Apache Cassandra VS Google Cloud PostgreSQL

Compare Apache Cassandra VS Google Cloud PostgreSQL and see what are their differences

Apache Cassandra logo Apache Cassandra

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

Google Cloud PostgreSQL logo Google Cloud PostgreSQL

Fully-managed database service
  • Apache Cassandra Landing page
    Landing page //
    2022-04-17
  • Google Cloud PostgreSQL Landing page
    Landing page //
    2023-09-29

Apache Cassandra features and specs

  • Scalability
    Apache Cassandra is designed for linear scalability and can handle large volumes of data across many commodity servers without a single point of failure.
  • High Availability
    Cassandra ensures high availability by replicating data across multiple nodes. Even if some nodes fail, the system remains operational.
  • Performance
    It provides fast writes and reads by using a peer-to-peer architecture, making it highly suitable for applications requiring quick data access.
  • Flexible Data Model
    Cassandra supports a flexible schema, allowing users to add new columns to a table at any time, making it adaptable for various use cases.
  • Geographical Distribution
    Data can be distributed across multiple data centers, ensuring low-latency access for geographically distributed users.
  • No Single Point of Failure
    Its decentralized nature ensures there is no single point of failure, which enhances resilience and fault-tolerance.

Possible disadvantages of Apache Cassandra

  • Complexity
    Managing and configuring Cassandra can be complex, requiring specialized knowledge and skills for optimal performance.
  • Eventual Consistency
    Cassandra follows an eventual consistency model, meaning that there might be a delay before all nodes have the latest data, which may not be suitable for all use cases.
  • Write-heavy Operations
    Although Cassandra handles writes efficiently, write-heavy workloads can lead to compaction issues and increased read latency.
  • Limited Query Capabilities
    Cassandra's query capabilities are relatively limited compared to traditional RDBMS, lacking support for complex joins and aggregations.
  • Maintenance Overhead
    Regular maintenance tasks such as node repair and compaction are necessary to ensure optimal performance, adding to the administrative overhead.
  • Tooling and Ecosystem
    While the ecosystem for Cassandra is growing, it is still not as extensive or mature as those for some other database technologies.

Google Cloud PostgreSQL features and specs

  • Scalability
    Google Cloud PostgreSQL offers easy scalability for growing databases, allowing you to adjust resources like CPU and RAM without significant downtime.
  • Managed Service
    As a fully managed service, it reduces the overhead of database maintenance tasks such as backups, patching, and updates, allowing developers to focus on application development.
  • High Availability
    It provides high availability configurations with automated failover to ensure that your database is reliable and your application remains uninterrupted.
  • Security
    Offers strong security measures, including encryption at rest and in transit, and integration with Google Cloud's Identity and Access Management (IAM).
  • Integration
    Seamlessly integrates with other Google Cloud services, making it easier to build comprehensive cloud solutions.

Possible disadvantages of Google Cloud PostgreSQL

  • Cost
    The cost can become high compared to other options, especially if your database requirements grow significantly, leading to increased resource allocation.
  • Limited Customization
    Being a managed service, there may be limited ability to customize certain configurations compared to self-hosted PostgreSQL solutions.
  • Vendor Lock-in
    Using Google Cloud services can lead to dependency on their ecosystem, making it challenging to migrate to another platform or cloud provider in the future.
  • Latency
    While Google Cloud provides robust infrastructure, network latency can still be an issue, especially if the service is being accessed from geographically distant regions.
  • Complexity
    Navigating and configuring the myriad of available options in Google Cloud can be complex and requires a certain level of expertise, which might be burdensome for newcomers.

Analysis of Apache Cassandra

Overall verdict

  • Apache Cassandra is an excellent choice if you require a database system that can efficiently manage large-scale data while ensuring high availability and reliability. It is particularly well-suited for use cases that demand a robust, distributed, and scalable database solution.

Why this product is good

  • Apache Cassandra is a highly scalable and distributed NoSQL database management system designed to handle large amounts of data across multiple commodity servers without a single point of failure. It offers robust support for replicating data across multiple data centers, thereby enhancing fault tolerance and availability. Its masterless architecture and linear scalability make it suitable for high throughput online transactional applications.

Recommended for

  • Applications that require high availability and fault tolerance
  • Systems with large volumes of write-heavy workloads
  • Organizations that need multi-data center replication
  • Businesses seeking a scalable solution for distributed databases
  • Use cases needing real-time data processing with low latency

Apache Cassandra videos

Course Intro | DS101: Introduction to Apache Cassandraโ„ข

More videos:

  • Review - Introduction to Apache Cassandraโ„ข

Google Cloud PostgreSQL videos

No Google Cloud PostgreSQL videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Apache Cassandra and Google Cloud PostgreSQL)
Databases
93 93%
7% 7
Developer Tools
0 0%
100% 100
NoSQL Databases
100 100%
0% 0
Relational Databases
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Cassandra and Google Cloud PostgreSQL

Apache Cassandra Reviews

Database Management Systems (DBMS) Comparison: SQL Server, MySQL, PostgreSQL, MongoDB, Oracle
Determine the type of data that your application will be handling. The options from the relational database list, like PostgreSQL or MySQL, are your top pick with structured data, while NoSQL options (MongoDB or Cassandra) are best used for unstructured or semi-structured data.
Source: blog.devart.com
20 Best Database Management Software and Tools of 2026
Apache Cassandra is a distributed database system designed for managing large volumes of structured data across multiple servers.
Source: infomineo.com
16 Top Big Data Analytics Tools You Should Know About
Application Areas: If you want to work with SQL-like data types on a No-SQL database, Cassandra is a good choice. It is a popular pick in the IoT, fraud detection applications, recommendation engines, product catalogs and playlists, and messaging applications, providing fast real-time insights.
9 Best MongoDB alternatives in 2019
The Apache Cassandra is an ideal choice for you if you want scalability and high availability without affecting its performance. This MongoDB alternative tool offers support for replicating across multiple datacenters.
Source: www.guru99.com

Google Cloud PostgreSQL Reviews

We have no reviews of Google Cloud PostgreSQL yet.
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Social recommendations and mentions

Based on our record, Apache Cassandra should be more popular than Google Cloud PostgreSQL. It has been mentiond 45 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.

Apache Cassandra mentions (45)

  • Why Apache IoTDB Is Written in Java: A Decade of Engineering Trade-offs
    When IoTDB was initiated in 2011, almost all influential distributed systems and databases were built in Java or on the JVMโ€”such as Hadoop, HBase, Spark (Scala on JVM), Cassandra, Kafka, and Flink. To integrate deeply with the big data ecosystem, choosing Java was a natural decision. - Source: dev.to / 3 months ago
  • Why You Shouldnโ€™t Invest In Vector Databases?
    In fact, even in the absence of these commercial databases, users can effortlessly install PostgreSQL and leverage its built-in pgvector functionality for vector search. PostgreSQL stands as the benchmark in the realm of open-source databases, offering comprehensive support across various domains of database management. It excels in transaction processing (e.g., CockroachDB), online analytics (e.g., DuckDB),... - Source: dev.to / about 1 year ago
  • Data integrity in Ably Pub/Sub
    All messages are persisted durably for two minutes, but Pub/Sub channels can be configured to persist messages for longer periods of time using the persisted messages feature. Persisted messages are additionally written to Cassandra. Multiple copies of the message are stored in a quorum of globally-distributed Cassandra nodes. - Source: dev.to / over 1 year ago
  • Which Database is Perfect for You? A Comprehensive Guide to MySQL, PostgreSQL, NoSQL, and More
    Cassandra is a highly scalable, distributed NoSQL database designed to handle large amounts of data across many commodity servers without a single point of failure. - Source: dev.to / about 2 years ago
  • Consistent Hashing: An Overview and Implementation in Golang
    Distributed storage Distributed storage systems like Cassandra, DynamoDB, and Voldemort also use consistent hashing. In these systems, data is partitioned across many servers. Consistent hashing is used to map data to the servers that store the data. When new servers are added or removed, consistent hashing minimizes the amount of data that needs to be remapped to different servers. - Source: dev.to / about 2 years ago
View more

Google Cloud PostgreSQL mentions (7)

  • Kubernetes and Container Portability: Navigating Multi-Cloud Flexibility
    Google Cloud SQL for MySQL (for managed MySQL) or Google Cloud SQL for PostgreSQL (for managed PostgreSQL). - Source: dev.to / about 1 year ago
  • Top 8 Managed Postgres Providers
    This is Google's managed service for databases that makes it easier to set up, maintain, and manage PostgreSQL databases on Google Cloud. - Source: dev.to / almost 2 years ago
  • Questions about 'databaseing' on the Cloud
    For a small database you don't need Snowflake. You need Postgres or MySQL. Power BI for visualizing data seems fine. For entering data you can use Airforms. Source: almost 3 years ago
  • Distributed Managed PostgreSQL Database Alternatives in the Cloud
    PostgreSQL is an open-source relational database, used by many companies, and is very common among cloud applications, where companies prefer an open-source solution, supported by a strong community, as an alternative to commercial database engines. The simplest way to run the PostgreSQL engine in the cloud is to choose one of the managed database services, such as Amazon RDS for PostgreSQL or Google Cloud SQL... - Source: dev.to / over 3 years ago
  • Get data from Cloud SQL with Python
    For the database, I used Cloud SQL, which is a managed database service from Google Cloud Platform (GCP). This GCP product provides a cloud-based alternative to MySQL, PostgreSQL and SQL Server databases. The great advantage of Cloud SQL is that it is a managed service, that is, you do not have to worry about some tasks related to the infrastructure where the database will run, tasks such as backups, maintenance... - Source: dev.to / about 4 years ago
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What are some alternatives?

When comparing Apache Cassandra and Google Cloud PostgreSQL, you can also consider the following products

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Supabase - An open source Firebase alternative

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

pREST - A fully RESTful API from any existing PostgreSQL database written in Go