DBMS > Apache Druid vs. FileMaker vs. IRONdb vs. RocksDB vs. RRDtool

System Properties Comparison Apache Druid vs. FileMaker vs. IRONdb vs. RocksDB vs. RRDtool

Editorial information provided by DB-Engines

Name

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

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Relational DBMS
Time Series DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

druid.apache.org

www.claris.com/filemaker

www.circonus.com/solutions/time-series-database/

rocksdb.org

oss.oetiker.ch/rrdtool

Technical documentation

druid.apache.org/docs/latest/design

www.claris.com/resources/documentation

docs.circonus.com/irondb/category/getting-started

github.com/facebook/rocksdb/wiki

oss.oetiker.ch/rrdtool/doc

Developer

Apache Software Foundation and contributors

Claris

a subsidiary of Apple

Circonus LLC.

Facebook, Inc.

Tobias Oetiker

Initial release

2012

1983

2017

2013

1999

Current release

29.0.1, April 2024

19.4.1, November 2021

V0.10.20, January 2018

9.2.1, May 2024

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

BSD

Open Source

GPL V2 and FLOSS

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 and C++

C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux
OS X
Unix

iOS

client part only
Linux
OS X
Windows

Linux

HP-UX
Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

Numeric data only

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.

yes

A http query request can return the data in XML format

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

via plugins

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Filemaker WebDirect
JDBC
ODBC

HTTP API

C++ API
Java API

in-process shared library
Pipes

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

PHP

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Go
Java
Perl
Python
Ruby

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Automatic, metric affinity per node

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication, warm standby

since Version 14

configurable replication factor, datacenter aware

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

simple rights management via user accounts and connection to external directory services

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.