DBMS > atoti vs. EventStoreDB vs. EXASOL vs. InfluxDB vs. Snowflake

System Properties Comparison atoti vs. EventStoreDB vs. EXASOL vs. InfluxDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

DBMS for storing time series, events and metrics

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	22.12
Rank	#28	Overall
	#1	Time Series DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

atoti.io

www.eventstore.com

www.exasol.com

www.influxdata.com/products/influxdb-overview

www.snowflake.com

Technical documentation

docs.atoti.io

developers.eventstore.com

www.exasol.com/resources

docs.influxdata.com/influxdb

docs.snowflake.net/manuals/index.html

Developer

ActiveViam

Event Store Limited

Exasol

Snowflake Computing Inc.

Initial release

2012

2000

2013

2014

Current release

21.2, February 2021

2.7.6, April 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux
Windows

Linux
OS X

through Homebrew

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL-like query language

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

HTTP API
JSON over UDP

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Python

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

in enterprise version only

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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, multi-version concurrency control (MVCC)

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.

yes

Depending on used storage engine

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

simple rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

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