DBMS > EsgynDB vs. LevelDB vs. RocksDB vs. Teradata vs. Weaviate

System Properties Comparison EsgynDB vs. LevelDB vs. RocksDB vs. Teradata vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

A hybrid cloud data analytics software platform (Teradata Vantage)

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

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

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

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.esgyn.cn

github.com/google/leveldb

rocksdb.org

www.teradata.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

github.com/facebook/rocksdb/wiki

docs.teradata.com

weaviate.io/developers/weaviate

Developer

Esgyn

Google

Facebook, Inc.

Teradata

Weaviate B.V.

Initial release

2015

2011

2013

1984

2019

Current release

1.23, February 2021

8.11.4, April 2024

Teradata Vantage 1.0 MU2, January 2019

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

BSD

commercial

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

C++, Java

C++

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Linux

hosted
Linux

Data scheme

yes

schema-free

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

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

SQL

Support of SQL

yes

SQL 2016 + extensions

GraphQL is used as query language

APIs and other access methods

ADO.NET
JDBC
ODBC

C++ API
Java API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Go
Java
Perl
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Sharding

Hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

yes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

with automatic compression on writes

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

fine grained access rights 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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