DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. GreptimeDB vs. HBase vs. Oracle Berkeley DB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. GreptimeDB vs. HBase vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

An open source Time Series DBMS built for increased scalability, high performance and efficiency

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

Widely used in-process key-value store

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

greptime.com

hbase.apache.org

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

docs.greptime.com

hbase.apache.org/book.html

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Greptime Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2016

2022

2008

1994

Current release

2.3.4, January 2021

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

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

Rust

Java

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
Unix
Windows

using Cygwin

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JDBC
ODBC

gRPC
HTTP API
JDBC

Java API
RESTful HTTP API
Thrift

Supported programming languages

C
Java
Perl
Python
R

C++
Erlang
Go
Java
JavaScript

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

Python

yes

Coprocessors in Java

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

Source-replica 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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

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

fine grained access rights according to SQL-standard

Simple rights management via user accounts

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

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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