DBMS > Oracle NoSQL vs. Splice Machine vs. SQLite vs. Weaviate

System Properties Comparison Oracle NoSQL vs. Splice Machine vs. SQLite vs. Weaviate

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Name

Description

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

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

Widely used embeddable, in-process RDBMS

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Document store
Key-value store
Relational DBMS

Relational DBMS

Vector DBMS

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

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

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

splicemachine.com

www.sqlite.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

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

splicemachine.com/how-it-works

www.sqlite.org/docs.html

weaviate.io/developers/weaviate

Developer

Oracle

Splice Machine

Dwayne Richard Hipp

Weaviate B.V.

Initial release

2011

2014

2000

2019

Current release

24.1, May 2024

3.1, March 2021

3.46.1 (13 August 2024), August 2024

1.19, May 2023

License

Commercial or Open Source

Open Source

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

Open Source

AGPL 3.0, commercial license available

Open Source

Public Domain

Open Source

commercial license available with Weaviate Enterprise

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

Server operating systems

Linux
Solaris SPARC/x86

Linux
OS X
Solaris
Windows

server-less

Data scheme

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

yes

dynamic column types

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

optional

yes

not rigid because of 'dynamic typing' concept.

yes

string, int, float, geo point, date, cross reference, fuzzy references

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

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

GraphQL is used as query language

APIs and other access methods

RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

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

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

JavaScript / TypeScript
Python

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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

Access rights for users and roles

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

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
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Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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