DBMS > Apache Drill vs. Postgres-XL vs. Tigris vs. Yaacomo

System Properties Comparison Apache Drill vs. Postgres-XL vs. Tigris vs. Yaacomo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store
Key-value store
Search engine
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

drill.apache.org

www.postgres-xl.org

www.tigrisdata.com

yaacomo.com

Technical documentation

drill.apache.org/docs

www.postgres-xl.org/documentation

www.tigrisdata.com/docs

Developer

Apache Software Foundation

Tigris Data, Inc.

Q2WEB GmbH

Initial release

2012

2014

since 2012, originally named StormDB

2022

2009

Current release

1.20.3, January 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Mozilla public license

Open Source

Apache Version 2.0

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

Server operating systems

Linux
OS X
Windows

Linux
macOS

Linux
macOS
Windows

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

CLI Client
gRPC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

C++

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

yes, using FoundationDB

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

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

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

Recent citations in the news

MapR to Speak on Stream Processing Systems, Apache Spark and Drill at Industry Events in January
31 May 2024, Yahoo Movies UK

Apache Drill vs. Apache Spark — Which SQL query engine is better for you?
23 September 2019, Towards Data Science

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

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

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

provided by Google News

Tigris Data Unveils Beta Launch of New Vector Search Tool
19 May 2023, Datanami

Tigris Data Launches All-in-One Developer Data Platform
27 September 2022, Datanami

FerretDB Provides Alternative to MongoDB
19 May 2023, Datanami

provided by Google News

Share this page