github.com/upmio

Open Source

We Code in the Open, We Build for Enterprise

Our code on GitHub ↗
§ 01

Open Source Needed

35%invest the most in databases and data technologies

Organizations are investing the most in Open Source databases and data technologies. Cloud and container (and container orchestration) technologies are still being heavily invested in by many organizations. Further analysis reveals that it is particularly large enterprises that are investing in the use of containers as the preferred architectural model while small to mid-size entities are allocating more to data technologies.

Which categories of open source software has your organization invested in the most in terms of projects, budget, and resources?
Databases and Data Technologies35%
Cloud and Container Technologies31.64%
Programming Languages and Frameworks31.50%
Operating Systems28.64%
DevOps/GitOps/DevSecOps Tooling26.93%
Analytics19.86%
Networking17.93%
Content Management Systems17.79%
Desktop and Personal Productivity15.86%
Security Tools14.50%
Software Development Life Cycle (SDLC) Tools13.57%
Frameworks and Tooling for AI/ML/DL11.14%
Observability Tools10.57%
Blockchain8.79%
Open Source Hardware8.36%
Middleware7.93%
Storage Technologies6.93%
Other4.36%

Source: 2024 State of Open Source Report — OpenLogic, Open Source Initiative, Eclipse Foundation

§ 02

Database Needed

40.2%use MySQL — 37% use PostgreSQL

The top two most used open source data technologies are MySQL and PostgreSQL. Some notable increases include Redis (almost 10% higher than last year), Apache Kafka, and Apache Spark. Redis now has more than a billion Docker Hub pulls and it has an engaged community of developers, architects, and open source contributors. Percentage of usage was static for both ElasticSearch and its open source fork, OpenSearch. PostgreSQL is used more commonly than MySQL. Both the largest and the smallest organizations prefer MySQL over PostgreSQL.

Source: 2024 State of Open Source Report (OpenLogic, Open Source Initiative, Eclipse Foundation)

Which open source data technologies does your organization use today?
MySQL40.20%
PostgreSQL37%
MariaDB27.06%
SQLite25.47%
MongoDB25.11%
Redis20.76%
ElasticSearch19.96%
Apache Kafka16.33%
Apache Hadoop10.47%
InfluxDB10.20%
Apache Spark10.12%
OpenSearch9.58%
Cassandra9.05%
Fluentd8.43%
Grafana Loki8.43%
Neo4j6.92%
Apache Solr6.83%
Apache Derby6.57%
Apache Flink6.39%
CouchDB6.12%
CockroachDB6.03%
Timescale5.24%
Hazelcast4.97%

Source: 2024 State of Open Source Report — OpenLogic, Open Source Initiative, Eclipse Foundation

§ 03

Adoption is Growing

63%use open source cloud / container technologies

Linux, cloud/container and database are the top 3 adopted Open Source technologies. Linux and cloud/container are the top 2 most contributed Open Source technologies. Both adoption and contribution are growing rapidly.

Source: World of Open Source Global Spotlight 2023 Report (The Linux Foundation)

In which of the following areas does your organization use / contribute to OSS?
Use OSSContribute to OSS
64%Linux34%
63%Cloud / Container technologies43%
54%Database and data management28%
54%CI / CD & DevOps31%
52%Web & application development35%
50%DevOps / GitOps / DevSecOps30%
43%Advanced analytics and data science33%
42%Kubernetes25%
41%Cybersecurity29%
40%Artificial Intelligence / Machine Learning31%
28%Storage technologies16%
26%IoT & Embedded19%
23%Networking technologies (5G, SDN, NFV, etc.)16%
20%Edge computing15%
16%Open source hardware16%
15%Blockchain15%
10%Augmented / Virtual reality9%
9%Manufacturing, 3D printing, and CAD / CAM7%
3%Other8%

Source: World of Open Source Global Spotlight 2023 — The Linux Foundation

§ 04

Data service on Kubernetes leads the way

97%run data-intensive workloads on cloud native platforms

Organizations everywhere are choosing to run their data on Kubernetes, with 97% choosing to run data-intensive workloads on their cloud native platforms. A significant number of critical applications like databases (72%), analytics (67%), and AI/ML workloads (54%) are being built on Kubernetes, further proving the maturity of Kubernetes. Managing these types of data-intensive workloads is no easy feat.

Source: The Voice of Kubernetes Experts Report 2024 (Portworx)

Does your organization run any of the following types of data services or workloads on Kubernetes environments?
Databases (NoSQL, SQL etc.)72%
Analytics (Data processing/ELT/ETL)67%
AI/ML (Artificial Intelligence or Machine Learning)54%
CI/CD pipeline54%
Persistent storage39%
We don't run any of these on Kubernetes3%

Source: The Voice of Kubernetes Experts Report 2024 — Portworx