DBMS > EJDB vs. EsgynDB vs. GreptimeDB vs. LevelDB vs. Weaviate

System Properties Comparison EJDB vs. EsgynDB vs. GreptimeDB vs. LevelDB vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

An open source Time Series DBMS built for increased scalability, high performance and efficiency

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

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

Primary database model

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

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

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

github.com/Softmotions/ejdb

www.esgyn.cn

greptime.com

github.com/google/leveldb

github.com/weaviate/weaviate
weaviate.io

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.greptime.com

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

weaviate.io/developers/weaviate

Developer

Softmotions

Esgyn

Greptime Inc.

Google

Weaviate B.V.

Initial release

2012

2015

2022

2011

2019

Current release

1.23, February 2021

1.19, May 2023

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache Version 2.0

Open Source

BSD

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

Rust

C++

Server operating systems

server-less

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

Illumos
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free, schema definition possible

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

yes

GraphQL is used as query language

APIs and other access methods

in-process shared library

ADO.NET
JDBC
ODBC

gRPC
HTTP API
JDBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

C++
Erlang
Go
Java
JavaScript

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

none

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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Simple rights management via user accounts

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

All companies that have data.
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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