HarperDB VS. MongoDB

HarperDB is the NoSQL document store that solves the problems that MongoDB couldn’t.

Game-Changing Throughput

Achieve more with orders of magnitude greater performance that drives down cost, latency, and complexity.

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Throughput Comparison (Drawn to Scale)

A throughput comparison showing that HarperDB can handle 15 times the write volume and 82 times the read volume per node when compared to MongoDB.

Performance Gives Simplicity Room to Flourish

HarperDB
Integrated In-Memory Cache
Integrated in-memory cache performs sub-millisecond lookups out of the box.
RESTful API in Seconds
A simple GraphQL-style schema definition creates a REST API that is simple, atomic, and fast. Plus, since every application already uses them, there is no learning curve.
NoSQL Flexibility with the Power of SQL
Normalized data is faster to write, faster to read, and easier to maintain. HarperDB lets you efficiently join tables with billions of records with nearly no performance trade-off and all the benefits of a traditional RDMS.
MongoDB
Solution Stacking
As performance lags, additional technologies like Redis are layered on top, adding complexity and cost.
Drivers are a Pain
Constant driver updates, saturated connections, and premature closes all make interacting with your data more complex than it needs to be.
The Prison of Denormalized at Scale
The simplicity of denormalized data presents challenges at scale. Size on disk becomes overwhelming, searching and updating nested attributes becomes expensive, and joins require costly application-level logic.

A Complete Solution

HarperDB unifies a high-performance database, user-programmed applications, and real-time data streaming in one technology. Unleashing system-wide efficiency MongoDB users could only dream of.

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Database

Lightning-fast document store is simple to manage and can handle orders of magnitude more throughput than alternatives.

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Application

Give your applications, APIs, and machine learning models direct data access, reducing latency beyond what data distribution can achieve.

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Streaming

Move data to and from devices and third-party systems on a publish and subscribe basis via MQTT, WebSocket, and HTTP interfaces.

Designed to Distribute

Every node of HarperDB is ready to publish and subscribe to every other node of HarperDB out-of-the-box and without additional services.

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Visual showing a globally distributed database

System Architecture Comparison

Architecture chart showing how simple distribution is with HarperDB's mesh network.Architecture chart showing how complex distribution is with MongoDB

Globally Simple

HarperDB
Scale Forever
Horizontal scale makes the cost of growth predictable and unlimited while naturally providing an opportunity for geo-distribution and decreased latency.
Reliable & Fast
Read and write failover instantly absorbed by other nodes + global distribution in as little as 100ms.
Full Copy or Table Level
Tailor what is replicated and when without needing additional servers, streamlining use cases in edge A.I., alerting, and even as a data streaming alternative.
MongoDB
Limited
Write volume limited to a single vertically scaled central database driving up costs and limiting throughput at scale.
Vulnerable & Slow
Numerous points of failure as data moves along a prescribed path between operation-exclusive servers. Common for data to take minutes, even hours, to replicate and become available.
Full Copy Only
Inflexible, all-or-nothing approach stymies innovation and contributes to an ever-growing backlog of technical debt.

Simple, Global, Cost-effective

Query with SQL

Quickly look up values without the need to learn MongoDB’s proprietary query language, MQL. Plus migrate from SQL databases without needing to rewrite every query.

Everywhere

Nodes of HarperDB can connect and synchronize data across your system architecture from edge devices to the centralized cloud, saving you time, effort, and money as you innovate.

Save Millions

All of the reasons above make HarperDB significantly more cost-efficient compared to MongoDB. Often, large enterprises save millions per year by switching.
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