Dragonflydb

Dragonflydb

Dragonfly - Scalable in-memory datastore made simple. Learn more

Launch date
Employees
Market cap
-
Enterprise valuation
€55—82m (Dealroom.co estimates Mar 2023.)
Tel Aviv-Yafo Tel Aviv District (HQ)
  • Edit
DateInvestorsAmountRound
-

N/A

-
*

$6.0m

Seed
*

N/A

-
*

$15.0m

Series A
Total Funding€19.1m

Recent News about Dragonflydb

Edit
More about Dragonflydbinfo icon
Edit

DragonflyDB.io is a technology startup that offers a simple, efficient, and cost-effective in-memory data store. It operates in the cloud computing market, serving developers and businesses that require high-performance data storage solutions. The company's primary product, Dragonfly, is fully compatible with Redis APIs, a popular in-memory data structure store, but eliminates the management complexities associated with Redis.

Dragonfly's business model is based on providing a superior alternative to traditional in-memory data stores like Redis. It leverages modern cloud computing capabilities to deliver 25 times more throughput and 12 times lower snapshotting latency. This means that Dragonfly can process more data and create backups faster than its competitors, providing a real-time experience that meets customer expectations.

Dragonfly also stands out for its reliability and scalability. It efficiently uses memory, reducing the risk of outages due to memory overload. It supports a primary-replica model, ensuring high availability of data. In case of an outage, Dragonfly automatically switches to the replica, promoting it as the primary. This system can handle workloads up to 1TB on a single instance, eliminating the fragility of distributed clusters and improving system reliability.

The company monetizes its services by offering a free trial version and presumably charging for more advanced features or larger storage capacities. However, specific details about its pricing strategy are not publicly available.

Keywords: Cloud Computing, In-Memory Data Store, High-Performance, Redis-Compatible, Cost-Efficient, High Throughput, Low Latency, Reliable, Scalable, Primary-Replica Model.