DBMS > Datomic vs. GigaSpaces vs. RocksDB vs. Snowflake vs. VelocityDB

System Properties Comparison Datomic vs. GigaSpaces vs. RocksDB vs. Snowflake vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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)

Cloud-based data warehousing service for structured and semi-structured data

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

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

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

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

Technical documentation

docs.datomic.com

docs.gigaspaces.com/latest/landing.html

github.com/facebook/rocksdb/wiki

docs.snowflake.net/manuals/index.html

velocitydb.com/UserGuide

Developer

Cognitect

Gigaspaces Technologies

Facebook, Inc.

Snowflake Computing Inc.

VelocityDB Inc

Initial release

2012

2000

2013

2014

2011

Current release

1.0.7075, December 2023

15.5, September 2020

9.2.1, May 2024

7.x

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

Java, C++, .Net

C++

Server operating systems

All OS with a Java VM

Linux
macOS
Solaris
Windows

Linux

hosted

Any that supports .NET

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

APIs and other access methods

RESTful HTTP API

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

C++ API
Java API

CLI Client
JDBC
ODBC

.Net

Supported programming languages

Clojure
Java

.Net
C++
Java
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

JavaScript (Node.js)
Python

.Net

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

user defined functions

Triggers

By using transaction functions

yes, event driven architecture

similar concept for controling cloud resources

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

horizontal partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Role-based access control

Users with fine-grained authorization concept, user roles and pluggable authentication

Based on Windows Authentication

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