DBMS > Apache Drill vs. FatDB vs. SingleStore vs. Yaacomo

System Properties Comparison Apache Drill vs. FatDB vs. SingleStore vs. Yaacomo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

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

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	5.91
Rank	#61	Overall
	#34	Relational DBMS

Website

drill.apache.org

www.singlestore.com

yaacomo.com

Technical documentation

drill.apache.org/docs

docs.singlestore.com

Developer

Apache Software Foundation

FatCloud

SingleStore Inc.

Q2WEB GmbH

Initial release

2012

2013

2009

Current release

1.20.3, January 2023

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free developer edition available

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C++, Go

Server operating systems

Linux
OS X
Windows

Windows

Linux

64 bit version required

Android
Linux
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

Via inetgration in SQL Server

yes

but no triggers and foreign keys

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

JDBC
ODBC

Supported programming languages

C++

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

via applications

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

hash partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

stores two copies of each physical data partition on two separate nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Can implement custom security layer via applications

Fine grained access control via users, groups and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more

Competitive advantages

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more

Typical application scenarios

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more

Key customers

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more

Market metrics

Customers in various industries worldwide including US and International Industry...
» more

Licensing and pricing models

F ree Tier and Enterprise Edition
» more

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022, Akmal Chaudhri, SingleStore (sponsor)

Cloud-Based Analytics With SingleStoreDB
9 June 2022, Akmal Chaudhri, SingleStore (sponsor)

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022, Akmal Chaudhri, SingleStore (sponsor)

show all

Recent citations in the news

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Using Apache Iceberg for Developing Modern Data Tables
3 October 2023, Open Source For You

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

provided by Google News

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

SingleStore Announces Exclusive Partnership with Agile Platform
15 April 2024, Business Wire

SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files
29 January 2024, Blocks & Files

Leveraging SingleStoreDB Cloud Private Connectivity Using AWS PrivateLink | Amazon Web Services
6 December 2023, AWS Blog

Announcing watsonx.ai and SingleStore for generative AI applications
15 November 2023, IBM

provided by Google News

Share this page