DBMS > Apache Drill vs. Faircom DB vs. TimesTen vs. YTsaurus

System Properties Comparison Apache Drill vs. Faircom DB vs. TimesTen vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Document store
Key-value store

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Score	0.15
Rank	#323	Overall
	#44	Document stores
	#47	Key-value stores

Website

drill.apache.org

www.faircom.com/products/faircom-db

www.oracle.com/database/technologies/related/timesten.html

ytsaurus.tech

Technical documentation

drill.apache.org/docs

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

docs.oracle.com/en/database/other-databases/timesten/index.html

ytsaurus.tech/docs/en

Developer

Apache Software Foundation

FairCom Corporation

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Yandex

Initial release

2012

1979

1998

2023

Current release

1.20.3, January 2023

V13, July 2024

Release 22.1

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Restricted, free version available

commercial

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

C++

Server operating systems

Linux
OS X
Windows

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

easily portable to other OSs

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Ubuntu

Data scheme

schema-free

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

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 SELECT statement is SQL:2003 compliant

yes, ANSI SQL with proprietary extensions

yes

YQL, an SQL-based language, is supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C++

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

C
C++
Java
Node.js
PL/SQL
Python

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

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

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Fine grained access rights according to SQL-standard with additional protections for files

fine grained access rights according to SQL-standard

Access Control Lists

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More resources

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