DBMS > Alibaba Cloud Table Store vs. Apache Druid vs. HBase vs. Postgres-XL vs. RavenDB

System Properties Comparison Alibaba Cloud Table Store vs. Apache Druid vs. HBase vs. Postgres-XL vs. RavenDB

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Wide column store

Relational DBMS
Time Series DBMS

Wide column store

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

www.alibabacloud.com/product/table-store

Technical documentation

www.alibabacloud.com/help/en/tablestore

druid.apache.org/docs/latest/design

hbase.apache.org/book.html

www.postgres-xl.org/documentation

ravendb.net/docs

Developer

Alibaba

Apache Software Foundation and contributors

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Hibernating Rhinos

Initial release

2016

2012

2008

2014

since 2012, originally named StormDB

2010

Current release

29.0.1, April 2024

2.3.4, January 2021

10 R1, October 2018

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

Apache version 2

Open Source

Mozilla public license

Open Source

AGPL version 3, commercial license available

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

Server operating systems

hosted

Linux
OS X
Unix

Linux
Unix
Windows

using Cygwin

Linux
macOS

Linux
macOS
Raspberry Pi
Windows

Data scheme

schema-free

yes

schema-less columns are supported

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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 for querying

yes

distributed, parallel query execution

SQL-like query language (RQL)

APIs and other access methods

HTTP API

JDBC
RESTful HTTP/JSON API

Java API
RESTful HTTP API
Thrift

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

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

Java
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

manual/auto, time-based

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

Multi-source replication

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

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

MVCC

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

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 rights based on subaccounts and tokens

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

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