DBMS > Apache Druid vs. Brytlyt vs. FileMaker vs. Heroic vs. RocksDB

System Properties Comparison Apache Druid vs. Brytlyt vs. FileMaker vs. Heroic vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Key-value store

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	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

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

Website

druid.apache.org

brytlyt.io

www.claris.com/filemaker

github.com/spotify/heroic

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

docs.brytlyt.io

www.claris.com/resources/documentation

spotify.github.io/heroic

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Brytlyt

Claris

a subsidiary of Apple

Spotify

Facebook, Inc.

Initial release

2012

2016

1983

2014

2013

Current release

29.0.1, April 2024

5.0, August 2023

19.4.1, November 2021

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++ and CUDA

Java

C++

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

iOS

client part only
Linux
OS X
Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

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.

yes

specific XML-type available, but no XML query functionality.

yes

A http query request can return the data in XML format

Secondary indexes

yes

via Elasticsearch

SQL

Support of SQL

SQL for querying

yes

via plugins

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Filemaker WebDirect
JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

PHP

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

Source-replica replication, warm standby

since Version 14

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

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

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

fine grained access rights according to SQL-standard

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

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