DBMS > Dragonfly vs. EsgynDB vs. TerarkDB vs. Vertica

System Properties Comparison Dragonfly vs. EsgynDB vs. TerarkDB vs. Vertica

Please select another system to include it in the comparison.

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

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

Spatial DBMS
Time Series DBMS

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

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

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

www.esgyn.cn

github.com/bytedance/terarkdb

www.vertica.com

Technical documentation

www.dragonflydb.io/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

vertica.com/documentation

Developer

DragonflyDB team and community contributors

Esgyn

ByteDance, originally Terark

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2023

2015

2016

2005

Current release

1.0, March 2023

12.0.3, January 2023

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

restricted open source version available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

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

C++

C++, Java

C++

Server operating systems

Linux

Data scheme

scheme-free

yes

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

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

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.

Secondary indexes

yes

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

SQL

Support of SQL

yes

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

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC

C++ API
Java API

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

character-based, interactive, front-end utility

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

All languages supporting JDBC/ODBC/ADO.Net

C++
Java

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

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

publish/subscribe channels provide some trigger functionality

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication between multi datacenters

none

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

yes

Bi-directional Spark integration

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

Concurrency

Support for concurrent manipulation of data

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

Password-based authentication

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

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, Business Wire

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

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

New Kubernetes Operator for Dragonfly In-Memory Datastore Now Available for Simplified Operations and Increased ...
18 April 2023, Business Wire

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

provided by Google News

A Chinese company is making the cloud 200x faster · TechNode
3 July 2017, TechNode

provided by Google News

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

How Embedded Analytics Help ISVs Overcome Challenges
14 September 2023, Spiceworks News and Insights

OpenText expands enterprise portfolio with AI and Micro Focus integrations
25 July 2023, VentureBeat

OpenText integrates Micro Focus tech through Cloud Editions 23.3
26 July 2023, Techzine Europe

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

provided by Google News

Share this page