Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

InfluxDB

1K
1.2K
+ 1
175
ToroDB

0
7
+ 1
0
Add tool

InfluxDB vs ToroDB: What are the differences?

What is InfluxDB? An open-source distributed time series database with no external dependencies. InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out..

What is ToroDB? Open source, document-oriented, JSON database that runs on top of PostgreSQL. ToroDB is an open source, document-oriented, JSON database that runs on top of PostgreSQL, providing storage and I/O savings and ACID semantics. ToroDB is MongoDB-compatible, so you can use Mongo clients to connect to it.

InfluxDB and ToroDB can be categorized as "Databases" tools.

Some of the features offered by InfluxDB are:

  • Time-Centric Functions
  • Scalable Metrics
  • Events

On the other hand, ToroDB provides the following key features:

  • Document-oriented (JSON)
  • Store data reliabily and durably with PostgreSQL
  • Use MongoDB clients to connect to it

InfluxDB and ToroDB are both open source tools. It seems that InfluxDB with 16.7K GitHub stars and 2.38K forks on GitHub has more adoption than ToroDB with 10 GitHub stars and 2 GitHub forks.

Advice on InfluxDB and ToroDB
Needs advice
on
HadoopHadoopInfluxDBInfluxDB
and
KafkaKafka

I have a lot of data that's currently sitting in a MariaDB database, a lot of tables that weigh 200gb with indexes. Most of the large tables have a date column which is always filtered, but there are usually 4-6 additional columns that are filtered and used for statistics. I'm trying to figure out the best tool for storing and analyzing large amounts of data. Preferably self-hosted or a cheap solution. The current problem I'm running into is speed. Even with pretty good indexes, if I'm trying to load a large dataset, it's pretty slow.

See more
Replies (1)
Recommends
on
DruidDruid

Druid Could be an amazing solution for your use case, My understanding, and the assumption is you are looking to export your data from MariaDB for Analytical workload. It can be used for time series database as well as a data warehouse and can be scaled horizontally once your data increases. It's pretty easy to set up on any environment (Cloud, Kubernetes, or Self-hosted nix system). Some important features which make it a perfect solution for your use case. 1. It can do streaming ingestion (Kafka, Kinesis) as well as batch ingestion (Files from Local & Cloud Storage or Databases like MySQL, Postgres). In your case MariaDB (which has the same drivers to MySQL) 2. Columnar Database, So you can query just the fields which are required, and that runs your query faster automatically. 3. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. 4. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures 5. Gives ana amazing centralized UI to manage data sources, query, tasks.

See more
Needs advice
on
InfluxDBInfluxDBMongoDBMongoDB
and
TimescaleDBTimescaleDB

We are building an IOT service with heavy write throughput and fewer reads (we need downsampling records). We prefer to have good reliability when comes to data and prefer to have data retention based on policies.

So, we are looking for what is the best underlying DB for ingesting a lot of data and do queries easily

See more
Replies (3)
Yaron Lavi
Recommends
on
PostgreSQLPostgreSQL

We had a similar challenge. We started with DynamoDB, Timescale, and even InfluxDB and Mongo - to eventually settle with PostgreSQL. Assuming the inbound data pipeline in queued (for example, Kinesis/Kafka -> S3 -> and some Lambda functions), PostgreSQL gave us a We had a similar challenge. We started with DynamoDB, Timescale and even InfluxDB and Mongo - to eventually settle with PostgreSQL. Assuming the inbound data pipeline in queued (for example, Kinesis/Kafka -> S3 -> and some Lambda functions), PostgreSQL gave us better performance by far.

See more
Recommends
on
DruidDruid

Druid is amazing for this use case and is a cloud-native solution that can be deployed on any cloud infrastructure or on Kubernetes. - Easy to scale horizontally - Column Oriented Database - SQL to query data - Streaming and Batch Ingestion - Native search indexes It has feature to work as TimeSeriesDB, Datawarehouse, and has Time-optimized partitioning.

See more
Ankit Malik
Software Developer at CloudCover · | 3 upvotes · 359K views
Recommends
on
Google BigQueryGoogle BigQuery

if you want to find a serverless solution with capability of a lot of storage and SQL kind of capability then google bigquery is the best solution for that.

See more
Decisions about InfluxDB and ToroDB
Benoit Larroque
Principal Engineer at Sqreen · | 2 upvotes · 147.6K views

I chose TimescaleDB because to be the backend system of our production monitoring system. We needed to be able to keep track of multiple high cardinality dimensions.

The drawbacks of this decision are our monitoring system is a bit more ad hoc than it used to (New Relic Insights)

We are combining this with Grafana for display and Telegraf for data collection

See more
Manage your open source components, licenses, and vulnerabilities
Learn More
Pros of InfluxDB
Pros of ToroDB
  • 59
    Time-series data analysis
  • 30
    Easy setup, no dependencies
  • 24
    Fast, scalable & open source
  • 21
    Open source
  • 20
    Real-time analytics
  • 6
    Continuous Query support
  • 5
    Easy Query Language
  • 4
    HTTP API
  • 4
    Out-of-the-box, automatic Retention Policy
  • 1
    Offers Enterprise version
  • 1
    Free Open Source version
    Be the first to leave a pro

    Sign up to add or upvote prosMake informed product decisions

    Cons of InfluxDB
    Cons of ToroDB
    • 4
      Instability
    • 1
      Proprietary query language
    • 1
      HA or Clustering is only in paid version
      Be the first to leave a con

      Sign up to add or upvote consMake informed product decisions

      - No public GitHub repository available -

      What is InfluxDB?

      InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

      What is ToroDB?

      ToroDB is an open source, document-oriented, JSON database that runs on top of PostgreSQL, providing storage and I/O savings and ACID semantics. ToroDB is MongoDB-compatible, so you can use Mongo clients to connect to it.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use InfluxDB?
      What companies use ToroDB?
        No companies found
        Manage your open source components, licenses, and vulnerabilities
        Learn More

        Sign up to get full access to all the companiesMake informed product decisions

        What tools integrate with InfluxDB?
        What tools integrate with ToroDB?

        Sign up to get full access to all the tool integrationsMake informed product decisions

        What are some alternatives to InfluxDB and ToroDB?
        TimescaleDB
        TimescaleDB: An open-source database built for analyzing time-series data with the power and convenience of SQL — on premise, at the edge, or in the cloud.
        Redis
        Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
        MongoDB
        MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
        Elasticsearch
        Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
        Prometheus
        Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.
        See all alternatives