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Cortex Project VS Presto DB

Compare Cortex Project VS Presto DB and see what are their differences

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NinjaOne (Formerly NinjaRMM) provides remote monitoring and management software that combines powerful functionality with a fast, modern UI. Easily remediate IT issues, automate common tasks, and support end-users with powerful IT management tools. featured
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Cortex Project logo Cortex Project

Horizontally scalable, highly available, multi-tenant, long term Prometheus.

Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)
  • Cortex Project Landing page
    Landing page //
    2023-01-04
  • Presto DB Landing page
    Landing page //
    2023-03-18

Cortex Project features and specs

  • Scalability
    Cortex is designed for high scalability, allowing it to handle extremely large volumes of metrics. It uses a distributed architecture that can scale horizontally by adding more nodes.
  • High Availability
    Cortex supports replication and redundancy, which ensure high availability of metric data. This means that even if some components fail, Cortex can continue to operate without data loss.
  • Multi-Tenancy
    The platform supports multi-tenancy, making it a good choice for organizations that need to manage and isolate metrics for different users or teams within the same infrastructure.
  • Compatibility with Prometheus
    Cortex is fully compatible with Prometheus, using the same querying language and client libraries. This allows for easy integration and migration from a Prometheus setup.
  • Long-Term Storage
    Unlike Prometheus, which is optimized for short-term storage, Cortex provides capabilities for long-term storage of metrics, useful for historical analysis and audits.

Possible disadvantages of Cortex Project

  • Complexity
    The distributed nature and the multitude of components in Cortex can make it complex to set up, configure, and maintain, especially for smaller teams with limited resources.
  • Resource Intensive
    Due to its architecture and capabilities, Cortex can be resource-intensive, requiring significant computational and storage infrastructure to operate efficiently.
  • Operational Overhead
    The operation of Cortex can introduce additional overhead, as it might require teams to manage additional services and configurations beyond what is needed for a standard Prometheus setup.
  • Steeper Learning Curve
    Users may face a steeper learning curve due to the distributed nature of the system and its configuration requirements, which can be challenging for newcomers.

Presto DB features and specs

  • High-Performance Query Engine
    Presto is designed for high-performance querying, capable of performing complex analytics and large-scale data processing at interactive speeds.
  • Distributed SQL Query Engine
    Presto can scale out to large clusters of machines, allowing for efficient distribution of queries over multiple servers to handle big data workloads.
  • Versatility
    Supports querying data from multiple data sources such as Hadoop, relational databases, NoSQL databases, and cloud object storage within a single query.
  • ANSI-SQL Compatibility
    Presto supports ANSI SQL, making it easier for users familiar with SQL to adapt and write queries without a steep learning curve.
  • Open Source
    Presto is an open-source project, which means it benefits from continuous community contributions and improvements, keeping it up-to-date and robust.
  • Extensible
    Presto's architecture is designed to be extensible, allowing users to add custom functions and connectors, tailored to specific needs.

Possible disadvantages of Presto DB

  • Resource Intensive
    High performance comes with significant resource requirements, necessitating robust infrastructure to realize its full potential.
  • Complex Configuration
    Setting up and configuring Presto can be complex and time-consuming, often requiring expertise and an understanding of its various components.
  • Limited Support for Transactions
    Presto is primarily designed for reading data and performing analytics, and it has limited support for transactional processing compared to traditional relational databases.
  • Community Support
    While it has a vibrant open-source community, users may find the support less comprehensive than that provided by commercial enterprise solutions.
  • Latency for Small Queries
    Designed for big data and complex queries, Presto may exhibit higher latency for small, simple queries compared to specialized databases optimized for such use cases.
  • Maintenance Overhead
    Managing and maintaining a Presto cluster can be labor-intensive, requiring ongoing tuning and maintenance to ensure optimal performance and reliability.

Analysis of Presto DB

Overall verdict

  • PrestoDB is considered a strong choice for organizations needing to perform fast and complex analytic queries. Its ability to execute SQL queries on big data at lightning speeds makes it an attractive tool for data-driven organizations. However, the choice of PrestoDB depends on specific use cases, existing infrastructure, and the team's familiarity with its architecture and operational demands.

Why this product is good

  • PrestoDB is a highly-regarded distributed SQL query engine that excels in speed and efficiency for querying large datasets. It's designed for running interactive analytic queries against data sources of all sizes. Some of its core strengths include its ability to query data across a wide variety of sources, scalability, and strong community support. It's often chosen for its capability to integrate seamlessly in environments requiring fast data processing and analysis without the need to move or transform data extensively.

Recommended for

    PrestoDB is ideal for technology firms, data-driven companies, and organizations in need of real-time data analytics. It is especially well-suited for those with existing big data frameworks (like Hadoop, Kafka, and Cassandra) who require a performant query engine to leverage large datasets efficiently. It's recommended for teams familiar with distributed systems who need the flexibility and speed offered by PrestoDB's architecture.

Category Popularity

0-100% (relative to Cortex Project and Presto DB)

Cortex Project

Presto DB

Monitoring Tools
100 100%
Monitoring Tools
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Databases
39 39%
Databases
61% 61
Database Tools
0 0%
Database Tools
100% 100

User comments

Share your experience with using Cortex Project and Presto DB. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Presto DB should be more popular than Cortex Project. It has been mentiond 10 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.

Cortex Project mentions (6)

  • Top 10 Prometheus Alternatives in 2024 [Includes Open-Source]
    Cortex is a horizontally scalable, highly available, multi-tenant prometheus alternative. - Source: dev.to / 12 months ago
  • Scaling Prometheus with Thanos
    There are many Projects like Thanos, M3, Cortex, and Victoriametrics. But Thanos is the most popular among these. Thanos addresses these issues with Prometheus and is the ideal solution for scaling Prometheus in environments with extensive metrics or multiple clusters where we require a global view of historical metrics. In this blog, we will explore the components of Thanos and will try to simplify its... - Source: dev.to / about 1 year ago
  • Self hosted log paraer
    Now if its more metric data you are using and want to do APM, prometheus is your man https://prometheus.io/, want to make prometheus your full time job? Deploy cortex https://cortexmetrics.io/, honorable mention in the metrics space, Zabbix, https://www.zabbix.com/ I've seen use cases of zabbix going way beyond its intended use its a fantastic tool. Source: over 2 years ago
  • Is anyone frustrated with anything about Prometheus?
    Yes, but also no. The Prometheus ecosystem already has two FOSS time-series databases that are complementary to Prometheus itself. Thanos and Mimir. Not to mention M3db, developed at Uber, and Cortex, then ancestor of Mimir. There's a bunch of others I won't mention as it would take too long. Source: over 2 years ago
  • Centralized solution for Prometheus?
    You can use the Remote write feature to send to a centralized location. It would have to be scalable like Cortex https://cortexmetrics.io/. Source: over 2 years ago
View more

Presto DB mentions (10)

  • Data Warehouses and Data Lakes: Understanding Modern Data Storage Paradigms 📦
    Follow Presto at Official Website, Linkedin, Youtube, and Slack channel to join the community. - Source: dev.to / 5 months ago
  • Introduction to Presto: Open Source SQL Query Engine that's changing Big Data Analytics
    In today's data-driven world, organizations face a constant challenge: how to analyse massive datasets quickly and efficiently without moving data between disparate systems. Presto, an open-source distributed SQL query engine that's revolutionizing how we approach big data analytics. - Source: dev.to / 5 months ago
  • Twitter's 600-Tweet Daily Limit Crisis: Soaring GCP Costs and the Open Source Fix Elon Musk Ignored
    Presto: Presto is an open-source distributed SQL query engine that enables querying data from various sources. It provides fast and interactive analytics capabilities, supporting a wide range of data formats and integration with different storage systems. - Source: dev.to / 6 months ago
  • Using IRIS and Presto for high-performance and scalable SQL queries
    The rise of Big Data projects, real-time self-service analytics, online query services, and social networks, among others, have enabled scenarios for massive and high-performance data queries. In response to this challenge, MPP (massively parallel processing database) technology was created, and it quickly established itself. Among the open-source MPP options, Presto (https://prestodb.io/) is the best-known... - Source: dev.to / 9 months ago
  • Parsing logs from multiple data sources with Ahana and Cube
    Presto is an open-source distributed SQL query engine, originally developed at Facebook, now hosted under the Linux Foundation. It connects to multiple databases or other data sources (for example, Amazon S3). We can use a Presto cluster as a single compute engine for an entire data lake. - Source: dev.to / over 3 years ago
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What are some alternatives?

When comparing Cortex Project and Presto DB, you can also consider the following products

Thanos.io - Open source, highly available Prometheus setup with long term storage capabilities.

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

Prometheus - An open-source systems monitoring and alerting toolkit.

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.

Grafana - Data visualization & Monitoring with support for Graphite, InfluxDB, Prometheus, Elasticsearch and many more databases

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.

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