DBMS > Axibase vs. Dragonfly vs. EsgynDB vs. Yaacomo

System Properties Comparison Axibase vs. Dragonfly vs. EsgynDB vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Key-value store

Relational DBMS

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Website

axibase.com/docs/atsd/finance

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

www.esgyn.cn

yaacomo.com

Technical documentation

www.dragonflydb.io/docs

Developer

Axibase Corporation

DragonflyDB team and community contributors

Esgyn

Q2WEB GmbH

Initial release

2013

2023

2015

2009

Current release

15585

1.0, March 2023

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

BSL 1.1

commercial

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

Java

C++

C++, Java

Server operating systems

Linux

Android
Linux
Windows

Data scheme

yes

scheme-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

Server-side scripts

Stored procedures

yes

Lua

Java Stored Procedures

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication between multi datacenters

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

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