DBMS > GeoMesa vs. LeanXcale vs. Postgres-XL vs. Solr vs. TempoIQ

System Properties Comparison GeoMesa vs. LeanXcale vs. Postgres-XL vs. Solr vs. TempoIQ

Editorial information provided by DB-Engines

Name

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

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

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

Primary database model

Spatial DBMS

Key-value store
Relational DBMS

Relational DBMS

Search engine

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

tempoiq.com (offline)

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

www.postgres-xl.org/documentation

solr.apache.org/resources.html

Developer

CCRi and others

LeanXcale

Apache Software Foundation

TempoIQ

Initial release

2014

2015

2014

since 2012, originally named StormDB

2006

2012

Current release

4.0.5, February 2024

10 R1, October 2018

9.6.0, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Mozilla public license

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

Scala

Java

Server operating systems

Linux
macOS

All OS with a Java VM

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

Data scheme

yes

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

schema-free

Typing

predefined data types such as float or date

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

through Apache Derby

yes

distributed, parallel query execution

Solr Parallel SQL Interface

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
RESTful HTTP/JSON API

HTTP API

Supported programming languages

C
Java
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Java plugins

Triggers

yes

User configurable commands triggered on index changes

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

optimistic locking

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

yes

simple authentication-based access control

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