DBMS > Apache Phoenix vs. Axibase vs. GeoSpock vs. RethinkDB vs. SAP HANA

System Properties Comparison Apache Phoenix vs. Axibase vs. GeoSpock vs. RethinkDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Spatial and temporal data processing engine for extreme data scale

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Secondary database models

Time Series DBMS

Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

phoenix.apache.org

axibase.com/docs/atsd/finance

geospock.com

rethinkdb.com

www.sap.com/products/hana.html

Technical documentation

phoenix.apache.org

rethinkdb.com/docs

help.sap.com/hana

Developer

Apache Software Foundation

Axibase Corporation

GeoSpock

The Linux Foundation

since July 2017

SAP

Initial release

2014

2013

2009

2010

Current release

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

15585

2.0, September 2019

2.4.1, August 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Java, Javascript

C++

Server operating systems

Linux
Unix
Windows

Linux

hosted

Linux
OS X
Windows

Appliance or cloud-service

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

string, binary, float, bool, date, geometry

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

temporal, categorical

yes

SQL

Support of SQL

yes

SQL-like query language

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

JDBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

JDBC
ODBC

Supported programming languages

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

Go
Java
PHP
Python
R
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

user defined functions

yes

SQLScript, R

Triggers

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

range based

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

User concepts

Access control

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

Access rights for users can be defined per table

yes

users and table-level permissions

yes

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