DBMS > Apache Impala vs. Postgres-XL vs. Titan vs. Yaacomo

System Properties Comparison Apache Impala vs. Postgres-XL vs. Titan vs. Yaacomo

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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.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Analytic DBMS for Hadoop

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

Titan is a Graph DBMS optimized for distributed clusters.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Website

impala.apache.org

www.postgres-xl.org

github.com/thinkaurelius/titan

yaacomo.com

Technical documentation

impala.apache.org/impala-docs.html

www.postgres-xl.org/documentation

github.com/thinkaurelius/titan/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Aurelius, owned by DataStax

Q2WEB GmbH

Initial release

2013

2014

since 2012, originally named StormDB

2012

2009

Current release

4.1.0, June 2022

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Mozilla public license

Open Source

Apache license, version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

Linux
macOS

Linux
OS X
Unix
Windows

Android
Linux
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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC
ODBC

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

via pluggable storage backends

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

yes

Transaction concepts

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

ACID

MVCC

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

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 for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services
24 August 2015, AWS Blog

Beyond Titan: The Evolution of DataStax's New Graph Database
21 June 2016, Datanami

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

DataStax acquires Aurelius, the startup behind the Titan graph database
3 February 2015, VentureBeat

DSE Graph review: Graph database does double duty
14 November 2019, InfoWorld

provided by Google News

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