DBMS > EventStoreDB vs. Heroic vs. Rockset vs. Vertica

System Properties Comparison EventStoreDB vs. Heroic vs. Rockset vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Column oriented

Secondary database models

Relational DBMS
Search engine

Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	1.07
Rank	#180	Overall
	#31	Document stores

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

www.eventstore.com

github.com/spotify/heroic

rockset.com

www.vertica.com

Technical documentation

developers.eventstore.com

spotify.github.io/heroic

docs.rockset.com

vertica.com/documentation

Developer

Event Store Limited

Spotify

Rockset

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2014

2019

2005

Current release

21.2, February 2021

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux
Windows

hosted

Linux

Data scheme

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

dynamic typing

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

ingestion from XML files supported

Secondary indexes

yes

via Elasticsearch

all fields are automatically indexed

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Read-only SQL queries, including JOINs

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP REST

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users and organizations can be defined via Rockset console

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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