DBMS > RavenDB vs. ReductStore vs. Splice Machine

System Properties Comparison RavenDB vs. ReductStore vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

Open Source Operational and Transactional Enterprise NoSQL Document Database

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

ravendb.net

github.com/reductstore
www.reduct.store

splicemachine.com

Technical documentation

ravendb.net/docs

www.reduct.store/docs

splicemachine.com/how-it-works

Developer

Hibernating Rhinos

ReductStore LLC

Splice Machine

Initial release

2010

2023

2014

Current release

5.4, July 2022

1.9, March 2024

3.1, March 2021

License

Commercial or Open Source

Open Source

AGPL version 3, commercial license available

Open Source

Business Source License 1.1

Open Source

AGPL 3.0, 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.

Implementation language

C++, Rust

Java

Server operating systems

Linux
macOS
Raspberry Pi
Windows

Docker
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (RQL)

yes

APIs and other access methods

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
JavaScript (Node.js)
Python
Rust

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Authorization levels configured per client per database

Access rights for users, groups and roles according to SQL-standard

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More resources

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