Vertica Accelerator Documentation

Vertica Accelerator offers managed Vertica databases, so you can leverage Vertica’s blazing speed without worrying about any of the setup, administration, or maintenance.

Database Tasks and Responsibilities

Major database management tasks are either automated or have dedicated Vertica experts.

Vertica (Self-managed) Vertica Accelerator (Managed by Vertica)
Installation & setup By user Guided by Vertica experts
Data loading & migration By user Guided by Vertica experts
Scaling By user Automated
Backup By user Automated
Node recovery By user Automated
Upgrade By user Upgrades by Vertica expert

How Vertica Accelerator works

Vertica Accelerator deploys resources in your own AWS account. The first user in your organization will need to set up cross-account linking with AWS using the IAM role. This grants permission for you to create, edit, and delete AWS resources linked to your Vertica Accelerator through our web-based UI. These permissions are strictly limited to your Vertica Accelerator resources.

For example, when you create a new database, Vertica Accelerator first deploys EC2 instances on the AWS. It then installs Vertica on the nodes and configures any settings such as CIDR access. This integration of both software configuration and hardware deployment by Vertica Accelerator enables you to easily manage your database with just a few clicks.


Vertica Accelerator is billed based on your vCPU usage. You will have a separate bill for AWS, which you pay AWS directly. With this, you can use your negotiated discounts, savings plans, and reserved instances on AWS.

You can monitor your usage on Vertica Accelerator as well as on AWS console.

Quick demo

Step-by-step guide

Step-by-step guide

Overview of Vertica Accelerator Features

Fast and easy database deployment and management – Simplified database tasks that can be easily accomplished with just a few clicks.

  • Create database
  • Create subcluster
  • Start & stop subcluster
  • Resize subcluster & edit EC2 instance type
  • Drop subcluster
  • Terminate & revive database
  • Idle shutdown
  • Backup & restore

Dynamically scale your clusters to meet your workload – the Accelerator uses Eon Mode so you can scale your database cluster up to meet increased workloads, or scale it down to save money.

  • Frequently fetched hot data are stored in the depot (SSD drives attached to the vCPU) for faster fetching, while cold data remains in S3 communal storage for cost savings.
  • Isolate your workload by creating multiple subclusters for dedicated resources so that bottleneck on one does not affect others.
  • Easily add or reduce compute resources by changing the number of nodes and the compute capacity of each node (EC2 instance size).
    • Scheduled autoscaling – Schedule your subcluster(s) to start and stop if you have a consistent workload.
    • Elastic autoscaling – Configure additional subclusters to start when your real-time workload exceeds a certain threshold. Conversely, stop subclusters when workload is low. This enables a good balance between cost and performance.

Vertica features

Vertica Accelerator deploys Vertica databases, so you also get the best of Vertica.

Columnar storage and execution - column stores offer significant gains in performance, I/O, storage footprint, and efficiency when it comes to analytic workloads. With columnar storage the query only reads the columns needed to answer the query.

Real-time loading and querying - with high query concurrency and the ability to simultaneously load new data into the system and querying it. Vertica can load data up to 10X faster than traditional row-store databases.

Advanced database analytics - a set of advanced in-database analytics including machine learning , geospatial , and time series analytics allows you to conduct the analytics computations closer to your data. These built-in features provide immediate results without having to resort to additional analytic tools.

Advanced compression - aggressive encoding and compression allows Vertica to dramatically improve analytic performance by reducing CPU, memory, and disk I/O at processing time. Vertica can reduce the original data size by up to 90%, to as little as 1/10th of its original size, without loss of information or precision.

Structured and semi-structured data - in addition to traditional structured database tables, Vertica provides flex tables that let you load and analyse semi-structured data such as data in JSON format.

Massively parallel processing - a robust and scalable parallel processing solution provides active redundancy, automatic replication, failover, and recovery.