DBMS > GeoMesa vs. LevelDB vs. Splice Machine vs. TempoIQ

System Properties Comparison GeoMesa vs. LevelDB vs. Splice Machine vs. TempoIQ

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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.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

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

Primary database model

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.geomesa.org

github.com/google/leveldb

splicemachine.com

tempoiq.com (offline)

Technical documentation

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

github.com/google/leveldb/blob/main/doc/index.md

splicemachine.com/how-it-works

Developer

CCRi and others

Google

Splice Machine

TempoIQ

Initial release

2014

2011

2014

2012

Current release

5.0.0, May 2024

1.23, February 2021

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

BSD

Open Source

AGPL 3.0, 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

Scala

C++

Java

Server operating systems

Illumos
Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

APIs and other access methods

JDBC
Native Spark Datasource
ODBC

HTTP API

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

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

simple authentication-based access control

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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