DBMS > Hypertable vs. SAP HANA vs. Snowflake vs. Solr vs. WakandaDB

System Properties Comparison Hypertable vs. SAP HANA vs. Snowflake vs. Solr vs. WakandaDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Cloud-based data warehousing service for structured and semi-structured data

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Spatial DBMS

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

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.sap.com/products/hana.html

www.snowflake.com

solr.apache.org

wakanda.github.io

Technical documentation

help.sap.com/hana

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

wakanda.github.io/doc

Developer

Hypertable Inc.

SAP

Snowflake Computing Inc.

Apache Software Foundation

Wakanda SAS

Initial release

2009

2010

2014

2006

2012

Current release

0.9.8.11, March 2016

2.0 SPS07 (April 4, 2023), April 2023

9.6.0, April 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Apache Version 2

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++, JavaScript

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Appliance or cloud-service

hosted

All OS with a Java VM

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

Linux
OS X
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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

yes

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

Secondary indexes

restricted

only exact value or prefix value scans

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

Solr Parallel SQL Interface

APIs and other access methods

C++ API
Thrift

JDBC
ODBC

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

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

JavaScript

Server-side scripts

Stored procedures

SQLScript, R

user defined functions

Java plugins

yes

Triggers

yes

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes

none

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

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.

yes

User concepts

Access control

yes

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

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