DBMS > Cachelot.io vs. HEAVY.AI vs. Ingres vs. SAP Advantage Database Server vs. TempoIQ

System Properties Comparison Cachelot.io vs. HEAVY.AI vs. Ingres vs. SAP Advantage Database Server vs. TempoIQ

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

In-memory caching system

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Well established RDBMS

Low-cost RDBMS with access to ISAM and FoxPro data structures

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

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Website

cachelot.io

github.com/heavyai/heavydb
www.heavy.ai

www.actian.com/databases/ingres

www.sap.com/products/advantage-database-server.html

tempoiq.com (offline)

Technical documentation

docs.heavy.ai

docs.actian.com/ingres

Developer

HEAVY.AI, Inc.

Actian Corporation

Sybase, SAP

TempoIQ

Initial release

2015

2016

1974

originally developed at University Berkely in early 1970s

1993

2012

Current release

5.10, January 2022

11.2, May 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache Version 2; enterprise edition 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

C++

C++ and CUDA

Server operating systems

FreeBSD
Linux
OS X

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
Windows

Data scheme

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Memcached protocol

JDBC
ODBC
Thrift
Vega

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

HTTP API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

Delphi
Perl
PHP

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Ingres Replicator

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

MVCC

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

caching of (temporary) tables can be configured

User concepts

Access control

fine grained access rights according to SQL-standard

simple authentication-based access control

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