DBMS > HugeGraph vs. ScyllaDB vs. SpaceTime vs. VoltDB

System Properties Comparison HugeGraph vs. ScyllaDB vs. SpaceTime vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Cassandra and DynamoDB compatible wide column store

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Key-value store

Relational DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.scylladb.com

www.mireo.com/spacetime

www.voltdb.com

Technical documentation

hugegraph.apache.org/docs

docs.scylladb.com

docs.voltdb.com

Developer

Baidu

ScyllaDB

Mireo

VoltDB Inc.

Initial release

2018

2015

2020

2010

Current release

0.9

ScyllaDB Open Source 5.4.1, January 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Open Source (AGPL), commercial license available

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java

C++

Java, C++

Server operating systems

Linux
macOS
Unix

Linux

Linux
OS X

for development

Data scheme

yes

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.

Secondary indexes

yes

also supports composite index and range index

yes

cluster global secondary indices

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL)

A subset of ANSI SQL is implemented

yes

only a subset of SQL 99

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

Proprietary protocol (CQL)

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

RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Groovy
Java
Python

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++
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes, Lua

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Fixed-grid hypercubes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

selectable replication factor

Representation of geographical distribution of servers is possible

Real-time block device replication (DRBD)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Users, roles and permissions

Access rights for users can be defined per object

yes

Users and roles with access to stored procedures

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,...
» 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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