DBMS > Amazon DocumentDB vs. Apache Druid vs. FileMaker vs. RocksDB vs. VictoriaMetrics

System Properties Comparison Amazon DocumentDB vs. Apache Druid vs. FileMaker vs. RocksDB vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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.

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Time Series DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

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	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

aws.amazon.com/documentdb

druid.apache.org

www.claris.com/filemaker

rocksdb.org

victoriametrics.com

Technical documentation

aws.amazon.com/documentdb/resources

druid.apache.org/docs/latest/design

www.claris.com/resources/documentation

github.com/facebook/rocksdb/wiki

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Apache Software Foundation and contributors

Claris

a subsidiary of Apple

Facebook, Inc.

VictoriaMetrics

Initial release

2019

2012

1983

2013

2018

Current release

29.0.1, April 2024

19.4.1, November 2021

9.2.1, May 2024

v1.91, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

Open Source

BSD

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Unix

iOS

client part only
Linux
OS X
Windows

Linux

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

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

A http query request can return the data in XML format

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

via plugins

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
RESTful HTTP/JSON API

Filemaker WebDirect
JDBC
ODBC

C++ API
Java API

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

PHP

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes, via HDFS, S3 or other storage engines

Source-replica replication, warm standby

since Version 14

yes

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

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

Access rights for users and roles

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

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