ClearDB vs TempoDB: What are the differences?
Developers describe ClearDB as "Fault tolerant database-as-a-service in the cloud for your MySQL powered applications". ClearDB uses a combination of advanced replication techniques, advanced cluster technology, and layered web services to provide you with a MySQL database that is "smarter" than usual. On the other hand, TempoDB is detailed as "Store & analyze time series data from sensors, smart meters, servers & more". TempoDB is the first database service for time series data (ex: measuring thermostat temperatures, network latencies, heart rates). Time series is a unique Big Data problem that breaks traditional databases (MySQL, MongoDB, etc). Today, businesses spend months and millions attempting to build solutions to manage all this data and yet still fail to store as much as they need or analyze it effectively. TempoDB is a purpose-built database service that enables businesses to store and analyze massive streams of time series data, so they can learn from the past, understand the present, and predict the future.
ClearDB and TempoDB can be primarily classified as "SQL Database as a Service" tools.
Some of the features offered by ClearDB are:
- Global Multi-Master Design- ClearDB uses geo-distributed MySQL database configurations for the ultimate in database availability, survivability, and performance. Even if whole cloud regions go offline, your database will stay online.
- Completely Fault Tolerant- ClearDB is the only cloud database in the market today that offers true multi-regional read/write mirroring with 100% uptime, even if networks or disks fail.
- Native MySQL- Our clusters use native MySQL so that you don't have to worry about re-tuning your applications to work with ClearDB.
On the other hand, TempoDB provides the following key features:
- Flexible, powerful API
- Store as much high resolution (1 ms max) time series data as you need for long range historical analysis
- We guarantee data availability and protect against loss by replicating each live datapoint 3x and using geographically distributed backup environments