DBMS > Alibaba Cloud TSDB vs. HBase vs. MySQL vs. Rockset vs. Solr

System Properties Comparison Alibaba Cloud TSDB vs. HBase vs. MySQL vs. Rockset vs. Solr

Editorial information provided by DB-Engines

Name

Description

A stable, reliable, and cost-effective online high-performance time series database service

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

Widely used open source RDBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Time Series DBMS

Wide column store

Relational DBMS

Key/Value like access via memcached API

Document store

Search engine

Secondary database models

Document store
Spatial DBMS

Relational DBMS
Search engine

Spatial DBMS

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

Score	0.24
Rank	#306	Overall
	#26	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.alibabacloud.com/product/hitsdb

Technical documentation

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

hbase.apache.org/book.html

dev.mysql.com/doc

docs.rockset.com

solr.apache.org/resources.html

Developer

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle

since 2010, originally MySQL AB, then Sun

Rockset

Apache Software Foundation

Initial release

2008

1995

2019

2006

Current release

2.3.4, January 2021

8.4.0, April 2024

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java

C and C++

C++

Java

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

FreeBSD
Linux
OS X
Solaris
Windows

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

schema-free, schema definition possible

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

Numeric data and Strings

options to bring your own types, AVRO

yes

dynamic typing

yes

supports customizable data types and automatic typing

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

ingestion from XML files supported

yes

Secondary indexes

yes

all fields are automatically indexed

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

Read-only SQL queries, including JOINs

Solr Parallel SQL Interface

APIs and other access methods

HTTP REST

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

Java API
RESTful HTTP/JSON API

Supported programming languages

Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
Java
JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

proprietary syntax

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

not for MyISAM storage engine

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

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

User concepts

Access control

Access managed on TSDB instance level

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

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and organizations can be defined via Rockset console

yes

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