DBMS > Alibaba Cloud Table Store vs. HBase vs. Newts vs. QuestDB vs. SQLite

System Properties Comparison Alibaba Cloud Table Store vs. HBase vs. Newts vs. QuestDB vs. SQLite

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Time Series DBMS based on Cassandra

A high performance open source SQL database for time series data

Widely used embeddable, in-process RDBMS

Primary database model

Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	2.70
Rank	#105	Overall
	#8	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.alibabacloud.com/product/table-store

hbase.apache.org

opennms.github.io/newts

questdb.io

www.sqlite.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

hbase.apache.org/book.html

github.com/OpenNMS/newts/wiki

questdb.io/docs

www.sqlite.org/docs.html

Developer

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Powerset

OpenNMS Group

QuestDB Technology Inc

Dwayne Richard Hipp

Initial release

2016

2008

2014

2000

Current release

2.3.4, January 2021

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Public Domain

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

Java

Java (Zero-GC), C++, Rust

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Linux
OS X
Windows

Linux
macOS
Windows

server-less

Data scheme

schema-free

schema-free, schema definition possible

schema-free

yes

schema-free via InfluxDB Line Protocol

yes

dynamic column types

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

not rigid because of 'dynamic typing' concept.

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 with time-series extensions

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

Java API
RESTful HTTP API
Thrift

HTTP REST
Java API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java
Python

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

horizontal partitioning (by timestamps)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication with eventual consistency

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

Single row ACID (across millions of columns)

ACID for single-table writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

through memory mapped files

yes

User concepts

Access control

Access rights based on subaccounts and tokens

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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