DBMS > AgensGraph vs. EXASOL vs. InfluxDB vs. Snowflake vs. Titan

System Properties Comparison AgensGraph vs. EXASOL vs. InfluxDB vs. Snowflake 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

Multi-model database supporting relational and graph data models and built upon PostgreSQL

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

DBMS for storing time series, events and metrics

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

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Graph DBMS
Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

bitnine.net/agensgraph

www.exasol.com

www.influxdata.com/products/influxdb-overview

www.snowflake.com

github.com/thinkaurelius/titan

Technical documentation

bitnine.net/documentation

www.exasol.com/resources

docs.influxdata.com/influxdb

docs.snowflake.net/manuals/index.html

github.com/thinkaurelius/titan/wiki

Developer

Bitnine Global Inc.

Exasol

Snowflake Computing Inc.

Aurelius, owned by DataStax

Initial release

2016

2000

2013

2014

2012

Current release

2.1, December 2018

2.7.6, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

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.

Implementation language

Java

Server operating systems

Linux
OS X
Windows

Linux
OS X

through Homebrew

hosted

Linux
OS X
Unix
Windows

Data scheme

depending on used data model

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

SQL-like query language

yes

APIs and other access methods

Cypher Query Language
JDBC

.Net
JDBC
ODBC
WebSocket

HTTP API
JSON over UDP

CLI Client
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
Java
JavaScript
Python

Java
Lua
Python
R

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

JavaScript (Node.js)
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

in enterprise version only

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

in enterprise version only

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

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.

yes

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

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

simple rights management via user accounts

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

User authentification and security via Rexster Graph Server

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