DBMS > Badger vs. Google Cloud Datastore vs. H2GIS vs. Sphinx vs. TempoIQ

System Properties Comparison Badger vs. Google Cloud Datastore vs. H2GIS vs. Sphinx vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Spatial extension of H2

Open source search engine for searching in data from different sources, e.g. relational databases

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Secondary database models

Relational DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

github.com/dgraph-io/badger

cloud.google.com/datastore

www.h2gis.org

sphinxsearch.com

tempoiq.com (offline)

Technical documentation

godoc.org/github.com/dgraph-io/badger

cloud.google.com/datastore/docs

www.h2gis.org/docs/home

sphinxsearch.com/docs

Developer

DGraph Labs

Google

CNRS

Sphinx Technologies Inc.

TempoIQ

Initial release

2017

2008

2013

2001

2012

Current release

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

LGPL 3.0

Open Source

GPL version 2, commercial licence 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

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes, details here

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

full-text index on all search fields

SQL

Support of SQL

SQL-like query language (GQL)

yes

SQL-like query language (SphinxQL)

APIs and other access methods

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

Proprietary protocol

HTTP API

Supported programming languages

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

Java

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

using Google App Engine

yes

based on H2

Triggers

Callbacks using the Google Apps Engine

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using Paxos

yes

based on H2

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

none

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.

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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)

yes

based on H2

simple authentication-based access control

More information provided by the system vendor

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Related products and services

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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