DBMS > Google Cloud Datastore vs. Machbase Neo vs. Solr vs. SpaceTime vs. Yaacomo

System Properties Comparison Google Cloud Datastore vs. Machbase Neo vs. Solr vs. SpaceTime vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

TimeSeries DBMS for AIoT and BigData

A widely used distributed, scalable search engine based on Apache Lucene

SpaceTime is a spatio-temporal DBMS with a focus on performance.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

cloud.google.com/datastore

machbase.com

solr.apache.org

www.mireo.com/spacetime

yaacomo.com

Technical documentation

cloud.google.com/datastore/docs

machbase.com/dbms

solr.apache.org/resources.html

Developer

Google

Machbase

Apache Software Foundation

Mireo

Q2WEB GmbH

Initial release

2008

2013

2006

2020

2009

Current release

V8.0, August 2023

9.6.1, May 2024

License

Commercial or Open Source

commercial

free test version available

Open Source

Apache Version 2

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

C++

Server operating systems

hosted

Linux
macOS
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Android
Linux
Windows

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes, details here

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language (GQL)

SQL-like query language

Solr Parallel SQL Interface

A subset of ANSI SQL is implemented

yes

APIs and other access methods

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

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

Java API
RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC

Supported programming languages

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C#
C++
Python

Server-side scripts

Stored procedures

using Google App Engine

Java plugins

Triggers

Callbacks using the Google Apps Engine

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Fixed-grid hypercubes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

selectable replication factor

yes

Real-time block device replication (DRBD)

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

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

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

volatile and lookup table

yes

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

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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Related products and services

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More resources

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