DBMS > Datomic vs. EJDB vs. GreptimeDB vs. KeyDB vs. Lovefield

System Properties Comparison Datomic vs. EJDB vs. GreptimeDB vs. KeyDB vs. Lovefield

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Embeddable relational database for web apps written in pure JavaScript

Primary database model

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

www.datomic.com

github.com/Softmotions/ejdb

greptime.com

github.com/Snapchat/KeyDB
keydb.dev

google.github.io/lovefield

Technical documentation

docs.datomic.com

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

docs.greptime.com

docs.keydb.dev

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Cognitect

Softmotions

Greptime Inc.

EQ Alpha Technology Ltd.

Google

Initial release

2012

2022

2019

2014

Current release

1.0.7075, December 2023

2.1.12, February 2017

License

Commercial or Open Source

commercial

limited edition free

Open Source

GPLv2

Open Source

Apache Version 2.0

Open Source

BSD-3

Open Source

Apache 2.0

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, Clojure

Rust

C++

JavaScript

Server operating systems

All OS with a Java VM

server-less

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-free

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

RESTful HTTP API

in-process shared library

gRPC
HTTP API
JDBC

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

Clojure
Java

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

C++
Erlang
Go
Java
JavaScript

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript

Server-side scripts

Stored procedures

yes

Transaction Functions

Python

Lua

Triggers

By using transaction functions

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

using MemoryDB

User concepts

Access control

Simple rights management via user accounts

simple password-based access control and ACL

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

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

Typical application scenarios

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

Key customers

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

Market metrics

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

Licensing and pricing models

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

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