DBMS > Axibase vs. Graph Engine vs. TempoIQ vs. Transbase vs. Vertica

System Properties Comparison Axibase vs. Graph Engine vs. TempoIQ vs. Transbase vs. Vertica

Editorial information provided by DB-Engines

Name

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

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

A resource-optimized, high-performance, universally applicable RDBMS

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Time Series DBMS

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

axibase.com/docs/atsd/finance

www.graphengine.io

tempoiq.com (offline)

www.transaction.de/en/products/transbase.html

www.vertica.com

Technical documentation

www.graphengine.io/docs/manual

www.transaction.de/en/products/transbase/features.html

vertica.com/documentation

Developer

Axibase Corporation

Microsoft

TempoIQ

Transaction Software GmbH

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2013

2010

2012

1987

2005

Current release

15585

Transbase 8.3, 2022

12.0.3, January 2023

License

Commercial or Open Source

commercial

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

Open Source

MIT License

commercial

free development license

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

.NET and C

C and C++

C++

Server operating systems

Linux

.NET

FreeBSD
Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

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

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like query language

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

RESTful HTTP API

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C#
C++
F#
Visual Basic

C#
Java
JavaScript

Node.js
Python
Ruby

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

Realtime Alerts

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

simple authentication-based access control

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

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

Recent citations in the news

The Ultimate ATV Test: Suzuki's King Quad 750 AXI Rugged Package vs. Alaska's Hunting Season
20 April 2021, Outdoor Life

provided by Google News

Trinity
2 June 2023, Microsoft

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

How Google and Microsoft taught search to "understand" the Web
6 June 2012, Ars Technica

provided by Google News

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

How Embedded Analytics Help ISVs Overcome Challenges
14 September 2023, Spiceworks News and Insights

OpenText expands enterprise portfolio with AI and Micro Focus integrations
25 July 2023, VentureBeat

OpenText integrates Micro Focus tech through Cloud Editions 23.3
26 July 2023, Techzine Europe

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

provided by Google News

Share this page