DBMS > Amazon CloudSearch vs. Databend vs. PostgreSQL vs. Titan

System Properties Comparison Amazon CloudSearch vs. Databend vs. PostgreSQL vs. Titan

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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

A hosted search engine service by Amazon with the data stored in Amazons cloud

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Search engine

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Graph DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.64
Rank	#135	Overall
	#12	Search engines

Score	0.27
Rank	#290	Overall
	#130	Relational DBMS

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Website

aws.amazon.com/cloudsearch

github.com/datafuselabs/databend
www.databend.com

www.postgresql.org

github.com/thinkaurelius/titan

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.databend.com

www.postgresql.org/docs

github.com/thinkaurelius/titan/wiki

Developer

Amazon

Databend Labs

PostgreSQL Global Development Group

www.postgresql.org/developer

Aurelius, owned by DataStax

Initial release

2012

2021

1989

1989: Postgres, 1996: PostgreSQL

2012

Current release

1.0.59, April 2023

16.4, August 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

BSD

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

Rust

Java

Server operating systems

hosted

hosted
Linux
macOS

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

yes

standard with numerous extensions

APIs and other access methods

HTTP API

CLI Client
JDBC
RESTful HTTP API

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

none

partitioning by range, list and (since PostgreSQL 11) by hash

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

none

Source-replica replication

other methods possible by using 3rd party extensions

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

authentication via encrypted signatures

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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