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VictoriaMetrics VS TimescaleDB

Compare VictoriaMetrics VS TimescaleDB and see what are their differences

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VictoriaMetrics logo VictoriaMetrics

Fast, easy-to-use, and cost-effective time series database

TimescaleDB logo TimescaleDB

TimescaleDB is a time-series SQL database providing fast analytics, scalability, with automated data management on a proven storage engine.
  • VictoriaMetrics Landing page
    Landing page //
    2022-08-08

VictoriaMetrics is a fast and scalable open source time series database and monitoring solution. It's designed to be user-friendly, allowing users to build a monitoring platform without scalability issues and with minimal operational burden. VictoriaMetrics is ideal for solving use cases with large amounts of time series data for IT infrastructure, APM, Kubernetes, IoT sensors, automotive vehicles, industrial telemetry, financial data, and other enterprise-level workloads. VictoriaMetrics is powered by several components, making it the perfect solution for collecting metrics (both push and pull models), running queries, and generating alerts. With VictoriaMetrics, you can store millions of data points per second on a single instance or scale to a high-load monitoring system across multiple data centers. Plus, it's designed to store 10x more data using the same compute and storage resources as existing solutions, making it a highly efficient choice. VictoriaMetrics boasts: Highest Ingestion Rate Fastest Query Performance Smallest Disk Storage Size Lowest Memory Usage Long-term Storage for Metrics Highly Scalable, Cloud Readiness Simple Set-up & Operation

  • TimescaleDB Landing page
    Landing page //
    2023-09-23

VictoriaMetrics

Website
victoriametrics.com
Pricing URL
Official VictoriaMetrics Pricing
$ Details
Startup details
Country
United States
State
California
City
San Francisco
Founder(s)
Aliaksandr Valialkin, Dzmitry (Dima) Lazerka, Roman Khavronenko, Artem Navoiev
Employees
20 - 49
Edit details

TimescaleDB

Website
timescale.com
Pricing URL
Official TimescaleDB Pricing
$ Details
Edit details

VictoriaMetrics features and specs

  • High Performance
    VictoriaMetrics is designed to handle large-scale loads efficiently, providing high performance for both data ingestion and query execution.
  • Scalability
    It supports horizontal scalability, making it suitable for growing workloads in distributed environments.
  • Cost-effective
    Optimized for low CPU and RAM usage, which helps in reducing overall infrastructure costs.
  • Compatibility
    Compatible with Prometheus, Grafana, and other tools in the Prometheus ecosystem, facilitating easy integration.
  • Multi-tenant Support
    Supports multi-tenancy, allowing multiple tenants to use the same setup without interference.
  • Single Node and Cluster Modes
    Offers flexibility to deploy in both single-node and cluster modes, adapting to various needs and scales.

Possible disadvantages of VictoriaMetrics

  • Learning Curve
    New users may encounter a steep learning curve, especially when transitioning from other time series databases.
  • Limited Ecosystem
    Although compatible with Prometheus, it has a smaller ecosystem and community support compared to more established solutions.
  • Feature Limitations
    Lacks some advanced features found in other time series databases, which might be a constraint for specific use cases.
  • Troubleshooting
    Users might find it challenging to troubleshoot and fine-tune performance without extensive documentation or community support.
  • Less Frequent Updates
    Compared to more mature projects, it might receive updates and new features less frequently.

TimescaleDB features and specs

  • Scalability
    TimescaleDB offers excellent horizontal and vertical scalability, which allows it to handle large volumes of data efficiently. Its architecture is designed to accommodate growth by distributing and efficiently managing data shards.
  • Time-Series Data Optimization
    Specifically optimized for time-series data, TimescaleDB provides features like hypertables and continuous aggregates that speed up queries and optimize storage for time-based data.
  • SQL Compatibility
    As an extension of PostgreSQL, TimescaleDB offers full SQL support, making it familiar to developers and allowing easy integration with existing SQL-based systems and applications.
  • Retention Policies
    TimescaleDB includes built-in data retention policies, enabling automatic management of historical data and freeing up storage by performing automatic data roll-ups or deletes.
  • Integration with the PostgreSQL Ecosystem
    It benefits from PostgreSQL's rich ecosystem of extensions, tools, and optimizations, allowing for versatile use cases beyond just time-series data while maintaining robust reliability and performance.

Possible disadvantages of TimescaleDB

  • Learning Curve
    Although it’s SQL-based, developers might face a learning curve to fully leverage TimescaleDB's time-series specific features such as hypertables and specific optimization techniques.
  • Limited Write Scalability
    While it's scalable, TimescaleDB might face challenges with extremely high-throughput write workloads compared to some NoSQL time-series databases, which are specifically built for such tasks.
  • Dependency on PostgreSQL
    As it operates as a PostgreSQL extension, any limitations and issues in PostgreSQL might directly affect TimescaleDB's performance and capabilities.
  • Complexity in Setup for High Availability
    Setting up TimescaleDB with high availability and distributed systems might introduce complexities, particularly for organizations that are not well-versed in PostgreSQL clustering and replication strategies.
  • Storage Overhead
    The additional storage features add an overhead, which means that while it adds value with its optimizations, users need to manage storage resources effectively, especially in environments with very large datasets.

VictoriaMetrics videos

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

Add video

TimescaleDB videos

+ Add

Rearchitecting a SQL Database for Time-Series Data | TimescaleDB

More videos:

  • Review - Visualizing Time-Series Data with TimescaleDB and Grafana

Category Popularity

0-100% (relative to VictoriaMetrics and TimescaleDB)

VictoriaMetrics

TimescaleDB

Monitoring Tools
100 100%
Monitoring Tools
0% 0
Databases
38 38%
Databases
62% 62
Time Series Database
40 40%
Time Series Database
60% 60
Relational Databases
0 0%
Relational Databases
100% 100

User comments

Share your experience with using VictoriaMetrics and TimescaleDB. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare VictoriaMetrics and TimescaleDB

VictoriaMetrics Reviews

Top 11 Grafana Alternatives & Competitors [2024]
VictoriaMetrics can be an alternative to Grafana Mimir which is focused on long-term storage of Prometheus. The same company has also launched VictoriaLogs which can be a good alternative to Grafana Loki.
Source: signoz.io

TimescaleDB Reviews

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 it’d be a great...
Source: pradeepchhetri.xyz
4 Best Time Series Databases To Watch in 2019
The Guardian did a very nice article explaining on they went from MongoDB to PostgresSQL in the favor of scaling their architecture and encrypting their content at REST. As you can tell, big companies are relying on SQL-constraint systems (with a cloud architecture of course) to ensure system reliability and accessibility. I believe that PostgresSQL will continue to grow, so...
Source: medium.com
20+ MongoDB Alternatives You Should Know About
TimescaleDB If on the other hand you are storing time series data in MongoDB, then TimescaleDB might be a good fit.
Source: www.percona.com

Social recommendations and mentions

Based on our record, VictoriaMetrics should be more popular than TimescaleDB. It has been mentiond 19 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.

VictoriaMetrics mentions (19)

  • 14 Monitoring Tools for Full-Stack Developers
    VictoriaMetrics is a monitoring tool and time series database. It is open-source and has a managed version. - Source: dev.to / 8 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 / 9 months ago
  • All you need is Wide Events, not "Metrics, Logs and Traces"
    Https://victoriametrics.com/ would definitely recommend anyone having performance issues with Prometheus to give VictoriaMetrics a try. - Source: Hacker News / about 1 year ago
  • Top 11 Grafana Alternatives in 2023
    VictoriaMetrics is primarily a time-series database designed for efficiently storing and querying time-series data. It is often used as a back-end data store for time-series data generated by monitoring systems like Prometheus. VictoriaMetrics excels at handling large volumes of time-series data, offering efficient storage and query capabilities. - Source: dev.to / over 1 year ago
  • InfluxDB CTO: Why We Moved from Go to Rust
    Not sure I follow since there are very competitive tools written in Go such as https://victoriametrics.com for an example in this space. - Source: Hacker News / over 1 year ago
View more

TimescaleDB mentions (5)

  • Ask HN: Does anyone use InfluxDB? Or should we switch?
    (:alert: I work for Timescale :alert:) It's funny, we hear this more and more "we did some research and landed on Influx and ... Help it's confusing". We actually wrote an article about what we think, you can find it here: https://www.timescale.com/blog/what-influxdb-got-wrong/ As the QuestDB folks mentioned if you want a drop in replacement for Influx then they would be an option, it kinda sounds that's not what... - Source: Hacker News / over 1 year ago
  • Best small scale dB for time series data?
    If you like PostgreSQL, I'd recommend starting with that. Additionally, you can try TimescaleDB (it's a PostgreSQL extension for time-series data with full SQL support) it has many features that are useful even on a small-scale, things like:. Source: over 2 years ago
  • Quick n Dirty IoT sensor & event storage (Django backend)
    I have built a Django server which serves up the JSON configuration, and I'd also like the server to store and render sensor graphs & event data for my Thing. In future, I'd probably use something like timescale.com as it is a database suited for this application. However right now I only have a handful of devices, and don't want to spend a lot of time configuring my back end when the Thing is my focus. So I'm... Source: over 3 years ago
  • How fast and scalable is TimescaleDB compare to a NoSQL Database?
    I've seen a lot of benchmark results on timescale on the web but they all come from timescale.com so I just want to ask if those are accurate. Source: over 3 years ago
  • The State of PostgreSQL 2021 Survey is now open!
    Ryan from Timescale here. We (TimescaleDB) just launched the second annual State of PostgreSQL survey, which asks developers across the globe about themselves, how they use PostgreSQL, their experiences with the community, and more. Source: about 4 years ago

What are some alternatives?

When comparing VictoriaMetrics and TimescaleDB, you can also consider the following products

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

InfluxData - Scalable datastore for metrics, events, and real-time analytics.

Levitate By Last9 - A managed time-series warehouse and end-to-end monitoring solution.

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

Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.

QuestDB - QuestDB is the fastest open source time series database

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