DBMS > Dragonfly vs. OpenTSDB vs. Warp 10 vs. Yaacomo

System Properties Comparison Dragonfly vs. OpenTSDB vs. Warp 10 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

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

Scalable Time Series DBMS based on HBase

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

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

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

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

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

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

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

opentsdb.net

www.warp10.io

yaacomo.com

Technical documentation

www.dragonflydb.io/docs

opentsdb.net/docs/build/html/index.html

www.warp10.io/content/02_Getting_started

Developer

DragonflyDB team and community contributors

currently maintained by Yahoo and other contributors

SenX

Q2WEB GmbH

Initial release

2023

2011

2015

2009

Current release

1.0, March 2023

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

LGPL

Open Source

Apache License 2.0

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

C++

Java

Server operating systems

Linux

Linux
Windows

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

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

numeric data for metrics, strings for tags

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

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

HTTP API
Telnet API

HTTP API
Jupyter
WebSocket

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

Lua

yes

WarpScript

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding

based on HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on HBase

selectable replication factor

based on HBase

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

based on HBase

Immediate Consistency

based on HBase

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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