DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon DynamoDB vs. HBase vs. Splice Machine vs. Titan

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon DynamoDB vs. HBase vs. Splice Machine vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Document store
Key-value store

Wide column store

Relational DBMS

Graph DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

aws.amazon.com/dynamodb

hbase.apache.org

splicemachine.com

github.com/thinkaurelius/titan

Technical documentation

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

docs.aws.amazon.com/dynamodb

hbase.apache.org/book.html

splicemachine.com/how-it-works

github.com/thinkaurelius/titan/wiki

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Splice Machine

Aurelius, owned by DataStax

Initial release

2016

2012

2008

2014

2012

Current release

2.3.4, January 2021

3.1, March 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache version 2

Open Source

AGPL 3.0, commercial license available

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

schema-free, schema definition possible

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

JDBC
Native Spark Datasource
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
Java
Perl
Python
R

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Java

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Yes, via Full Spark Integration

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

Access rights for users, groups and roles according to SQL-standard

User authentification and security via Rexster Graph Server

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