DBMS > Apache Phoenix vs. GeoMesa vs. Splice Machine

System Properties Comparison Apache Phoenix vs. GeoMesa vs. Splice Machine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

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

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

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

Score	1.91
Rank	#126	Overall
	#59	Relational DBMS

Score	0.80
Rank	#208	Overall
	#4	Spatial DBMS

Score	0.54
Rank	#246	Overall
	#114	Relational DBMS

Website

phoenix.apache.org

www.geomesa.org

splicemachine.com

Technical documentation

phoenix.apache.org

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

splicemachine.com/how-it-works

Developer

Apache Software Foundation

CCRi and others

Splice Machine

Initial release

2014

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

5.0.0, May 2024

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Scala

Java

Server operating systems

Linux
Unix
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

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

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

Server-side scripts

Stored procedures

user defined functions

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

depending on storage layer

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

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)

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

depending on storage layer

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

yes

depending on the DBMS used for storage

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

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

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

show all

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix
2 June 2016, AWS Blog

Deep dive into Azure HDInsight 4.0
25 September 2018, Microsoft

Hortonworks Starts Hadoop Summit with Data Platform Update
28 June 2016, ADT Magazine

Apache Drill Adds New Data Formats
28 March 2022, iProgrammer

Amazon EMR 4.7.0 – Apache Tez & Phoenix, Updates to Existing Apps
2 June 2016, AWS Blog

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine Learning
19 January 2021, PR Newswire

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Splice Machine Unveils Version 1.5 of Hadoop RDBMS with Expanded SQL Compliance
20 October 2015, Database Trends and Applications

provided by Google News

Share this page