DBMS > GigaSpaces vs. Oracle NoSQL vs. RocksDB vs. SurrealDB vs. TypeDB

System Properties Comparison GigaSpaces vs. Oracle NoSQL vs. RocksDB vs. SurrealDB vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

A fully ACID transactional, developer-friendly, multi-model DBMS

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Document store
Key-value store
Relational DBMS

Key-value store

Document store
Graph DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Graph DBMS
Search engine

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

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

www.gigaspaces.com

www.oracle.com/database/nosql/technologies/nosql

rocksdb.org

surrealdb.com

typedb.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

github.com/facebook/rocksdb/wiki

surrealdb.com/docs

typedb.com/docs

Developer

Gigaspaces Technologies

Oracle

Facebook, Inc.

SurrealDB Ltd

Vaticle

Initial release

2000

2011

2013

2022

2016

Current release

15.5, September 2020

23.3, December 2023

9.2.1, May 2024

v1.5.0, May 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

BSD

Open Source

GPL Version 3, commercial licenses 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.

Implementation language

Java, C++, .Net

Java

C++

Rust

Java

Server operating systems

Linux
macOS
Solaris
Windows

Linux
Solaris SPARC/x86

Linux

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

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

RESTful HTTP API

C++ API
Java API

GraphQL
RESTful HTTP API
WebSocket

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

.Net
C++
Java
Python
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

Deno
Go
JavaScript (Node.js)
Rust

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

with Hadoop integration

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

substituted by the relationship feature

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

yes

ACID

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

off heap cache

yes

User concepts

Access control

Role-based access control

Access rights for users and roles

yes, based on authentication and database rules

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

Apache f or language drivers, and AGPL and Commercial for the database server. The...
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