DBMS > AnzoGraph DB vs. Fauna vs. ScyllaDB vs. SiriDB

System Properties Comparison AnzoGraph DB vs. Fauna vs. ScyllaDB vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Cassandra and DynamoDB compatible wide column store

Open Source Time Series DBMS

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Wide column store

Time Series DBMS

Secondary database models

Key-value store

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

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.55
Rank	#154	Overall
	#26	Document stores
	#14	Graph DBMS
	#72	Relational DBMS
	#13	Time Series DBMS

Score	5.27
Rank	#67	Overall
	#5	Wide column stores

Score	0.11
Rank	#346	Overall
	#32	Time Series DBMS

Website

cambridgesemantics.com/anzograph

fauna.com

www.scylladb.com

siridb.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.fauna.com

docs.scylladb.com

docs.siridb.com

Developer

Cambridge Semantics

Fauna, Inc.

ScyllaDB

Cesbit

Initial release

2018

2014

2015

2017

Current release

2.3, January 2021

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Open Source (AGPL), commercial license available

Open Source

MIT License

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.

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

Scala

C++

Server operating systems

Linux

hosted

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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.

Secondary indexes

yes

cluster global secondary indices

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like DML and DDL statements (CQL)

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

RESTful HTTP API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

HTTP API

Supported programming languages

C++
Java
Python

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

yes, Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

selectable replication factor

Representation of geographical distribution of servers is possible

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

in-memory tables

yes

User concepts

Access control

Access rights for users and roles

Identity management, authentication, and access control

Access rights for users can be defined per object

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more

Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
» more

Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
» more

Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more

Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more

Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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