DBMS > DolphinDB vs. Dragonfly vs. ToroDB vs. VictoriaMetrics

System Properties Comparison DolphinDB vs. Dragonfly vs. ToroDB vs. VictoriaMetrics

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Secondary database models

Relational DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

www.dolphindb.com

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

github.com/torodb/server

victoriametrics.com

Technical documentation

docs.dolphindb.cn/en/help200/index.html

www.dragonflydb.io/docs

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

DolphinDB, Inc

DragonflyDB team and community contributors

8Kdata

VictoriaMetrics

Initial release

2018

2023

2016

2018

Current release

v2.00.4, January 2022

1.0, March 2023

v1.91, May 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

BSL 1.1

Open Source

AGPL-V3

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

Linux
Windows

Linux

All OS with a Java 7 VM

FreeBSD
Linux
macOS
OpenBSD

Data scheme

yes

scheme-free

schema-free

Typing

predefined data types such as float or date

yes

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

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

Proprietary protocol

RESP - REdis Serialization Protocol

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

Server-side scripts

Stored procedures

yes

Lua

Triggers

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Atomic execution of command blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

User concepts

Access control

Administrators, Users, Groups

Password-based authentication

Access rights for users and roles

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

DragonflyDB Announces $21m in New Funding and General Availability
21 March 2023, businesswire.com

DragonflyDB reels in $21M for its speedy in-memory database
21 March 2023, SiliconANGLE News

Dragonfly 1.0 Released For What Claims To Be The World's Fastest In-Memory Data Store
20 March 2023, Phoronix

Intel Linux Kernel Optimizations Show Huge Benefit For High Core Count Servers
29 March 2023, Phoronix

SFU Computing Science researchers receive 2022 ACM SIGMOD Research Highlight Award.
24 February 2023, Simon Fraser University News

provided by Google News

OpenTelemetry Is Too Complicated, VictoriaMetrics Says
1 April 2024, Datanami

KubeCon24: VictoriaMetrics' Simpler Alternative to Prometheus
20 March 2024, The New Stack

VictoriaMetrics Slashes Data Storage Bills by 90% With World's Most Cost-Efficient Monitoring
30 May 2024, Yahoo Finance

How VictoriaMetrics' open source approach led to mass industry adoption
3 May 2024, Tech.eu

VictoriaMetrics takes organic growth over investor pressure
11 December 2023, The Register

provided by Google News

Share this page