DBMS > Apache Drill vs. Cassandra vs. Snowflake vs. SwayDB vs. Titan

System Properties Comparison Apache Drill vs. Cassandra vs. Snowflake vs. SwayDB 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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Cloud-based data warehousing service for structured and semi-structured data

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Document store
Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

github.com/thinkaurelius/titan

Technical documentation

drill.apache.org/docs

cassandra.apache.org/doc/latest

docs.snowflake.net/manuals/index.html

github.com/thinkaurelius/titan/wiki

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Snowflake Computing Inc.

Simer Plaha

Aurelius, owned by DataStax

Initial release

2012

2008

2014

2018

2012

Current release

1.20.3, January 2023

4.1.3, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

commercial

Open Source

GNU Affero GPL V3.0

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

Providers of DBaaS offerings, please contact us to be listed.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Scala

Java

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Windows

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

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

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like SELECT, DML and DDL statements (CQL)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

CLI Client
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C++

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Java
Kotlin
Scala

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

yes

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes

none

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

none

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

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

Atomicity and isolation are supported for single operations

ACID

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

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.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Access rights for users can be defined per object

Users with fine-grained authorization concept, user roles and pluggable authentication

User authentification and security via Rexster Graph Server

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

News

GitHub Copilot + DataStax Astra DB: Build GenAI Apps 100x Faster
21 May 2024

Empowering On-Premises Deployments with Generative AI: Introducing Vector Search for a Self-Managed Modern Architecture
15 May 2024

Tips and Tricks for the DataStax Astra CLI
7 May 2024

How to Build a Crystal Image Search App with Vector Search
25 April 2024

Knowledge Graphs for RAG without a GraphDB
18 April 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.