DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. LMDB vs. STSdb vs. Transwarp ArgoDB

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. LMDB vs. STSdb vs. Transwarp ArgoDB

Editorial information provided by DB-Engines

Name

Description

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Secondary database models

Search engine

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

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

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.07
Rank	#350	Overall
	#153	Relational DBMS

Website

cloud.google.com/datastore

www.hawkular.org

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

github.com/STSSoft/STSdb4

www.transwarp.cn/en/product/argodb

Technical documentation

cloud.google.com/datastore/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

www.lmdb.tech/doc

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Google

Community supported by Red Hat

Symas

STS Soft SC

Transwarp

Initial release

2008

2014

2011

Current release

0.9.32, January 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

commercial

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

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
Unix
Windows

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

SQL-like query language (GQL)

yes

APIs and other access methods

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

HTTP REST

.NET Client API

Supported programming languages

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

Go
Java
Python
Ruby

.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#
Java

Server-side scripts

Stored procedures

using Google App Engine

Triggers

Callbacks using the Google Apps Engine

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

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

More information provided by the system vendor

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

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Best cloud storage of 2024
21 May 2024, TechRadar

Google Cloud Stops Exit Fees
12 January 2024, Spiceworks News and Insights

BigID Data Intelligence Platform Now Available on Google Cloud Marketplace
6 November 2023, PR Newswire

Google says it'll stop charging fees to transfer data out of Google Cloud
11 January 2024, TechCrunch

What is Google App Engine? | Definition from TechTarget
26 April 2024, TechTarget

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

The Tom Brady Data Biography
8 September 2023, StatsBomb

Automating SAP S/4HANA Migration with IT-Conductor, BGP Managed Services, and AWS | Amazon Web Services
22 August 2023, AWS Blog

The Lightning Memory-mapped Database
2 March 2016, InfoQ.com

Akamai launches managed database service – Blocks and Files
25 April 2022, Blocks & Files

Connecting the worlds of metabolomics databases
15 June 2021, Medical Xpress

provided by Google News

Share this page