DBMS > AnzoGraph DB vs. EJDB vs. ScyllaDB vs. SiteWhere

System Properties Comparison AnzoGraph DB vs. EJDB vs. ScyllaDB vs. SiteWhere

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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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Cassandra and DynamoDB compatible wide column store

M2M integration platform for persisting/querying time series data

Primary database model

Secondary database models

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	0.27
Rank	#297	Overall
	#44	Document stores

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

cambridgesemantics.com/anzograph

github.com/Softmotions/ejdb

www.scylladb.com

github.com/sitewhere/sitewhere

Technical documentation

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

github.com/Softmotions/ejdb/blob/master/README.md

docs.scylladb.com

sitewhere1.sitewhere.io/index.html

Developer

Cambridge Semantics

Softmotions

ScyllaDB

SiteWhere

Initial release

2018

2012

2015

2010

Current release

2.3, January 2021

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

GPLv2

Open Source

Open Source (AGPL), commercial license available

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

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

C++

Java

Server operating systems

Linux

server-less

Linux

Linux
OS X
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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 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

in-process shared library

Proprietary protocol (CQL)

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

HTTP REST

Supported programming languages

C++
Java
Python

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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, Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

selectable replication factor

Representation of geographical distribution of servers is possible

selectable replication factor

based on HBase

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

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

typically not needed, however similar functionality with collection joins possible

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

Read/Write Locking

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

Access rights for users can be defined per object

Users with fine-grained authorization concept

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...
» 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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