DBMS > Google Cloud Datastore vs. KeyDB vs. LMDB vs. Machbase Neo vs. Sadas Engine

System Properties Comparison Google Cloud Datastore vs. KeyDB vs. LMDB vs. Machbase Neo vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

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

A high performant, light-weight, embedded key-value database library

TimeSeries DBMS for AIoT and BigData

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

cloud.google.com/datastore

github.com/Snapchat/KeyDB
keydb.dev

www.symas.com/symas-embedded-database-lmdb

machbase.com

www.sadasengine.com

Technical documentation

cloud.google.com/datastore/docs

docs.keydb.dev

www.lmdb.tech/doc

machbase.com/dbms

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Google

EQ Alpha Technology Ltd.

Symas

Machbase

SADAS s.r.l.

Initial release

2008

2019

2011

2013

2006

Current release

0.9.32, January 2024

V8.0, August 2023

8.0

License

Commercial or Open Source

commercial

Open Source

BSD-3

Open Source

commercial

free test version available

commercial

free trial version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

Linux

Linux
Unix
Windows

Linux
macOS
Windows

AIX
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

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

SQL-like query language (GQL)

SQL-like query language

yes

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Proprietary protocol

RESP - REdis Serialization Protoco

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

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

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

using Google App Engine

Lua

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

Multi-source replication
Source-replica replication

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

volatile and lookup table

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

simple password-based access control and ACL

simple password-based access control

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

More information provided by the system vendor

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Related products and services

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