DBMS > OrigoDB vs. Prometheus vs. SAP HANA vs. Sqrrl

System Properties Comparison OrigoDB vs. Prometheus vs. SAP HANA vs. Sqrrl

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

A fully ACID in-memory object graph database

Open-source Time Series DBMS and monitoring system

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Object oriented DBMS

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

origodb.com

prometheus.io

www.sap.com/products/hana.html

sqrrl.com

Technical documentation

origodb.com/docs

prometheus.io/docs

help.sap.com/hana

Developer

Robert Friberg et al

SAP

Amazon

originally Sqrrl Data, Inc.

Initial release

2009

under the name LiveDB

2015

2010

2012

Current release

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

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

Server operating systems

Linux
Windows

Appliance or cloud-service

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

User defined using .NET types and collections

Numeric data only

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.

can be achieved using .NET

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
HTTP API
LINQ

RESTful HTTP/JSON API

JDBC
ODBC

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

.Net

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

Sharding

yes

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

by Federation

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

yes

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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