Sold by: quasardb
Deployed on AWS
AWS Free Tier
High performance time series database
4.3
Overview
QuasarDB is a high performance, distributed, transactional, time series database. It can ingest data at very high speed, while giving you immediate access through a powerful, SQL-like, query language. QuasarDB was designed to withstand the most extreme use case that can be found in financial markets, aeronautics, and heavy industry.
Highlights
- Speed, power, convenience, safety
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Debian 13
Deployed on AWS
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Pricing
This product is available free of charge. Free subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimensions summary
quasarDB Community Edition is free software. You pay nothing for the license itself. Pricing here reflects only the AWS EC2 instance you choose to run it on, billed hourly. Each dimension maps to a specific instance type from the t3, c5, c6a, c6i, m5, m6a, m6i, r6a, and r6i families. These families differ in CPU, memory, and size, from small t3.nano options to large metal and 48xlarge instances. You select the instance that fits your workload; hourly cost scales with the instance size and family you pick.
Top-of-mind questions for buyers
quasarDB Community Edition is free software, so the license adds no charge. Each hourly rate reflects only the AWS EC2 instance you run it on. You pay for one running instance per hour, based on the instance type you select from the listed families.
The software license is free, so no license charge applies whether the instance runs or not. Hourly charges here reflect the running EC2 instance. A stopped instance stops accruing instance-hour charges, though attached AWS storage may still incur separate storage fees.
The families differ in CPU-to-memory balance and size. The c-families favor compute-heavy work, m-families balance compute and memory, r-families favor memory-heavy work, and t3 suits small or variable workloads. Sizes range from nano up to metal and 48xlarge, so cost scales with the size you choose.
doc.quasar.ai
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Protocol version 49 [api] Bulk readers can now read metadata columns without selecting data columns [api] Add APIs to control asynchronous pipeline flushing and inspect the queue length [api] Add APIs to retrieve a tables shard size and list of shards [api] Add support for Arrow streams in bulk readers and batch writers [api] Bulk readers now return symbol columns as strings [api] Bulk readers preserve explicitly requested column order and support selecting $table and $timestamp [api] Fix batch splitting and handling of empty batches [api] Fix error reporting in qdb_exp_batch_push APIs [api] Fix schema validation when creating missing tables during batch insertion [api] Improve bulk reader performance and support for infinite shard sizes [api] Increase the maximum user property size to 64KiB [api] Random bulk readers now support aggregated tables and pending asynchronous writes [compatibility] Remove deprecated single-column and legacy ts_batch APIs [compatibility] Remove obsolete asynchronous pipeline queue length and old-data cutoff settings [compatibility] Remove protocol compatibility messages for versions older than 3.14.2 [kernel] Add a configurable limit on the number of rows per table shard [kernel] Add support for non-timeseries tables [kernel] Data in asynchronous pipelines is now immediately available to queries, including deduplicated writes [kernel] Fix a crash during prefix index lookups [kernel] Fix deleted table entries being restored in the in-memory index on reload [kernel] Fix replication when the number of entries exceeds the replication batch size [kernel] Fix symbol table recreation after purging the cluster [kernel] Improve asynchronous pipeline statistics and fix timestamp counts [kernel] Reject asynchronous writes when the disk is full [kernel] Reject legacy single-column writes that cannot preserve table alignment [linux] Include the static C API library in Linux packages [linux] Remove runtime dependencies on third-party shared libraries from the C API library [logging] Always rotate server log files on startup [logging] Fix dropped messages in asynchronous logging [logging] Improve slow query and batch writer logging [logging] Respect POSIX permissions and default ACLs when creating log files [orderbook] Improve memory usage and result processing [orderbook] Support COLLAPSED_DIFF_ONLY mode [persistence] Add a metric to track local SST cache usage [persistence] Add configurable minimum levels for SST partitioning during compaction [query] Add support for $rowid [query] Add support for exporting query results to CSV, TSV, and Parquet with COPY SELECT [query] Add support for importing Parquet files with configurable compression codecs and levels for Parquet exports [query] Allow the IMPORT timestamp column to be specified by name or index [query] ALTER TABLE TTL no longer immediately deletes expired data, reducing the load of TTL changes [query] Automatically generate user IDs when creating users [query] Fix a crash when resolving null symbols and a memory leak during symbol resolution [query] Fix GROUP BY $timestamp with LIMIT omitting rows from the selected groups [query] Fix parsing of string values that resemble dates [query] Fix range alignment when using WITH_DAY_START [query] Greatly improve aggregation performance and memory usage, including high-cardinality groups [query] Improve CSV import performance and option parsing [query] Improve SELECT performance by using the tables shard index [query] REPAIR can now rebuild the prefix index [query] SUM over an empty range now consistently returns NULL [query] Support setting, listing, and removing user properties through the query language [query] Support string concatenation in INSERT value expressions [shell] Add commands to control asynchronous pipeline flushing and inspect the queue length [shell] Add raw table and symbol table import/export commands [shell] Fix crashes on exit, including when reaching the connection limit [shell] Make the connection soft limit configurable and increase its default from 8 to 16 [windows] Add support for the Windows time zone database
Additional details
Usage instructions
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QuasarDB runs as a systemd service, you can inspect its status as follows:
systemctl status qdbd.service
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An exported of QuasarDB metrics to Amazon Cloudwatch has been preinstalled and configured as a systemd service. You can inspect its status as follows:
systemctl status qdb-cloudwatch.timer systemctl status qdb-cloudwatch.service
In order for the exporter to work, it requires the relevant IAM permissions assigned to this EC2's instance role.
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To connect to your QuasarDB instance, you can use qdbsh:
qdbsh qdb://127.0.0.1:2836
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For security purposes, QuasarDB only listens to localhost by default.
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You can configure and customize your QuasarDB installation by editing the configuration file at /etc/qdb/qdbd.conf.
For more information about QuasarDB, please consult the documentation available online at https://doc.quasar.ai/
For support, please contact us at support@quasar.ai .
Resources
Vendor resources
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Joel F.
A clear breakthrough in timeseries database
Reviewed on Apr 01, 2019
Review provided by G2
What do you like best about the product?
QuasarDB is a clear innovation. QuasarDB enables you to store massive amount of data without sacrificing on query speed.
The level of performances that one can leverage is clearly at least one order of magnitude over a lot of competitors. From
the large selection of platforms and languages to high-performance compression features, it really simplifies
the management of large scale databases.
A must-have if performances on your whole stack is a required.
The level of performances that one can leverage is clearly at least one order of magnitude over a lot of competitors. From
the large selection of platforms and languages to high-performance compression features, it really simplifies
the management of large scale databases.
A must-have if performances on your whole stack is a required.
What do you dislike about the product?
No major roadblocks even if in some places the query error messages are sometimes unclear
What problems is the product solving and how is that benefiting you?
- HPC research on large datasets
- Storage of HPC datasets
- Storage of HPC datasets
Financial Services
a great analytics platform when high performance needed.
Reviewed on Mar 18, 2019
Review provided by G2
What do you like best about the product?
The software development team, really go deep on optimization and software quality, exploiting the best of Intel CPU. Very very few software platform are going that way, which explain the performance of the platform.
What do you dislike about the product?
no major roadblock, user interface cam always be improved.
What problems is the product solving and how is that benefiting you?
Nice platform for Financial market place process/data. Anything requesting near real time analytics.
Recommendations to others considering the product:
nice player, when needing near real time analytics.
Information Technology and Services
High performance timeseries database that is great with numbers
Reviewed on Mar 16, 2019
Review provided by G2
What do you like best about the product?
The performance of numerical calculations is superb -- when offloading calculations / aggregates to the database, it is able to achieve stellar performance.
What do you dislike about the product?
It takes some time to learn how to use it. The UI is very unforgiving sometimes, although it does seem to get better with every release.
What problems is the product solving and how is that benefiting you?
We moved from InfluxDB, and especially exploring our dataset has been much easier: the speed of the engine make it easy to interactively test and iterate on your queries.
Recommendations to others considering the product:
Make sure your data is mostly numerical, this is where you will be seeing the most benefits of using QuasarDB.