DBMS > Axibase vs. Dragonfly vs. Google Cloud Firestore vs. KairosDB vs. SQLite

System Properties Comparison Axibase vs. Dragonfly vs. Google Cloud Firestore vs. KairosDB vs. SQLite

Editorial information provided by DB-Engines

Name

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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Distributed Time Series DBMS based on Cassandra or H2

Widely used embeddable, in-process RDBMS

Primary database model

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

axibase.com/docs/atsd/finance

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

firebase.google.com/products/firestore

github.com/kairosdb/kairosdb

www.sqlite.org

Technical documentation

www.dragonflydb.io/docs

firebase.google.com/docs/firestore

kairosdb.github.io

www.sqlite.org/docs.html

Developer

Axibase Corporation

DragonflyDB team and community contributors

Google

Dwayne Richard Hipp

Initial release

2013

2023

2017

2013

2000

Current release

15585

1.0, March 2023

1.2.2, November 2018

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

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

Open Source

BSL 1.1

commercial

Open Source

Apache 2.0

Open Source

Public Domain

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

Java

C++

Java

Server operating systems

Linux

hosted

Linux
OS X
Windows

server-less

Data scheme

yes

scheme-free

schema-free

yes

dynamic column types

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

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Java
JavaScript

Node.js
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Lua

yes, Firebase Rules & Cloud Functions

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

via file-system locks

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

simple password-based access control

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