DBMS > Alibaba Cloud Table Store vs. Apache Drill vs. InfluxDB vs. Linter vs. Newts

System Properties Comparison Alibaba Cloud Table Store vs. Apache Drill vs. InfluxDB vs. Linter vs. Newts

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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

DBMS for storing time series, events and metrics

RDBMS for high security requirements

Time Series DBMS based on Cassandra

Primary database model

Wide column store

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

drill.apache.org

www.influxdata.com/products/influxdb-overview

linter.ru

opennms.github.io/newts

Technical documentation

www.alibabacloud.com/help/en/tablestore

drill.apache.org/docs

docs.influxdata.com/influxdb

github.com/OpenNMS/newts/wiki

Developer

Alibaba

Apache Software Foundation

relex.ru

OpenNMS Group

Initial release

2016

2012

2013

1990

2014

Current release

1.20.3, January 2023

2.7.6, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
OS X

through Homebrew

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

SQL-like query language

yes

APIs and other access methods

HTTP API

JDBC
ODBC
RESTful HTTP API

HTTP API
JSON over UDP

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

HTTP REST
Java API

Supported programming languages

Java
Python

C++

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Java

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

in enterprise version only

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

in enterprise version only

Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Depending on the underlying data source

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

Depending on used storage engine

User concepts

Access control

Access rights based on subaccounts and tokens

Depending on the underlying data source

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

News

An Introductory Guide to Grafana Alerts
16 May 2024

What is DevRel at InfluxData
14 May 2024

What to Expect When You’re Expecting InfluxDB: A Guide
14 May 2024

Introduction to Apache Iceberg
9 May 2024

Converting Timestamp to Date in Java
7 May 2024

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

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Apache Software Foundation Announces New Top-Level Project Apache Paimon
16 April 2024, Datanami

Top data analytics tools comparison: Alibaba Cloud, AWS, Azure, Google Cloud, IBM
5 December 2019, Wire19

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

25 Best Cloud Service Providers (Public and Private) in 2024
4 June 2023, CybersecurityNews

Apache Software Foundation Announces New Top-Level Project Apache Paimon
19 April 2024, Datanami

provided by Google News

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

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

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

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

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

provided by Google News

Introducing Amazon Timestream for InfluxDB: A managed service for the popular open source time-series database ...
20 May 2024, AWS Blog

Amazon Timestream: Managed InfluxDB for Time Series Data
14 March 2024, The New Stack

InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World
14 March 2024, Business Wire

How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency
15 March 2024, Datanami

Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services
14 March 2024, AWS Blog

provided by Google News

Share this page