DBMS > Drizzle vs. GigaSpaces vs. RocksDB vs. ScyllaDB

System Properties Comparison Drizzle vs. GigaSpaces vs. RocksDB vs. ScyllaDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Cassandra and DynamoDB compatible wide column store

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Wide column store

Secondary database models

Graph DBMS
Search engine

Key-value store

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

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Website

www.gigaspaces.com

rocksdb.org

www.scylladb.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

github.com/facebook/rocksdb/wiki

docs.scylladb.com

Developer

Drizzle project, originally started by Brian Aker

Gigaspaces Technologies

Facebook, Inc.

ScyllaDB

Initial release

2008

2000

2013

2015

Current release

7.2.4, September 2012

15.5, September 2020

9.2.1, May 2024

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD

Open Source

Open Source (AGPL), commercial license available

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.

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Implementation language

C++

Java, C++, .Net

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

cluster global secondary indices

SQL

Support of SQL

yes

with proprietary extensions

SQL-99 for query and DML statements

SQL-like DML and DDL statements (CQL)

APIs and other access methods

JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

C++ API
Java API

Proprietary protocol (CQL)

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

Supported programming languages

C
C++
Java
PHP

.Net
C++
Java
Python
Scala

C
C++
Go
Java
Perl
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

yes

yes, Lua

Triggers

hooks for callbacks inside the server can be used.

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role-based access control

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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