DBMS > Dragonfly vs. InfluxDB vs. LevelDB vs. Postgres-XL vs. Snowflake

System Properties Comparison Dragonfly vs. InfluxDB vs. LevelDB vs. Postgres-XL vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

DBMS for storing time series, events and metrics

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Secondary database models

Spatial DBMS

with GEO package

Document store
Spatial DBMS

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.influxdata.com/products/influxdb-overview

github.com/google/leveldb

www.postgres-xl.org

www.snowflake.com

Technical documentation

www.dragonflydb.io/docs

docs.influxdata.com/influxdb

github.com/google/leveldb/blob/main/doc/index.md

www.postgres-xl.org/documentation

docs.snowflake.net/manuals/index.html

Developer

DragonflyDB team and community contributors

Google

Snowflake Computing Inc.

Initial release

2023

2013

2011

2014

since 2012, originally named StormDB

2014

Current release

1.0, March 2023

2.7.6, April 2024

1.23, February 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD

Open Source

Mozilla public license

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

C++

Server operating systems

Linux

Linux
OS X

through Homebrew

Illumos
Linux
OS X
Windows

Linux
macOS

hosted

Data scheme

scheme-free

schema-free

yes

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

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

HTTP API
JSON over UDP

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

user defined functions

Triggers

publish/subscribe channels provide some trigger functionality

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

none

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

in enterprise version only

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Password-based authentication

simple rights management via user accounts

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

News

Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS
29 May 2024

Using Parquet’s Bloom Filters
28 May 2024

Efficiency Unleashed: Streamlining Workflows with the InfluxDB Management API
23 May 2024

What is DevRel at InfluxData
21 May 2024

An Introductory Guide to Grafana Alerts
16 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.