DBMS > AnzoGraph DB vs. IRONdb vs. SAP HANA vs. ScyllaDB

System Properties Comparison AnzoGraph DB vs. IRONdb vs. SAP HANA vs. ScyllaDB

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

In-memory, column based data store. Available as appliance or cloud service

Cassandra and DynamoDB compatible wide column store

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Key-value store

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Website

cambridgesemantics.com/anzograph

www.circonus.com/solutions/time-series-database/

www.sap.com/products/hana.html

www.scylladb.com

Technical documentation

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

docs.circonus.com/irondb/category/getting-started

help.sap.com/hana

docs.scylladb.com

Developer

Cambridge Semantics

Circonus LLC.

SAP

ScyllaDB

Initial release

2018

2017

2010

2015

Current release

2.3, January 2021

V0.10.20, January 2018

2.0 SPS07 (April 4, 2023), April 2023

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

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

Server operating systems

Linux

Appliance or cloud-service

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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.

Secondary indexes

yes

cluster global secondary indices

SQL

Support of SQL

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

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

HTTP API

JDBC
ODBC

Proprietary protocol (CQL)

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

Supported programming languages

C++
Java
Python

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

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

Server-side scripts

Stored procedures

user defined functions and aggregates

yes, in Lua

SQLScript, R

yes, Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Automatic, metric affinity per node

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

configurable replication factor, datacenter aware

yes

selectable replication factor

Representation of geographical distribution of servers is possible

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 per node, eventual consistency across nodes

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

User concepts

Access control

Access rights for users and roles

yes

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

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