DBMS > Apache Druid vs. Faircom DB vs. RocksDB vs. SpatiaLite vs. Yaacomo

System Properties Comparison Apache Druid vs. Faircom DB vs. RocksDB vs. SpatiaLite vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

Spatial extension of SQLite

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

Primary database model

Relational DBMS
Time Series DBMS

Key-value store
Relational DBMS

Key-value store

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

druid.apache.org

www.faircom.com/products/faircom-db

rocksdb.org

www.gaia-gis.it/fossil/libspatialite/index

yaacomo.com

Technical documentation

druid.apache.org/docs/latest/design

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

github.com/facebook/rocksdb/wiki

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Apache Software Foundation and contributors

FairCom Corporation

Facebook, Inc.

Alessandro Furieri

Q2WEB GmbH

Initial release

2012

1979

2013

2008

2009

Current release

29.0.1, April 2024

V12, November 2020

8.11.4, April 2024

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Restricted, free version available

Open Source

BSD

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

Java

ANSI C, C++

C++

Server operating systems

Linux
OS X
Unix

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

server-less

Android
Linux
Windows

Data scheme

yes

schema-less columns are supported

schema free, schema optional, schema required, partial schema,

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

SQL for querying

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

C++ API
Java API

JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

none

Source-replica replication

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
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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 with additional protections for files

fine grained access rights according to SQL-standard

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