DBMS > Axibase vs. Dgraph vs. Rockset vs. SAP HANA vs. Vertica

System Properties Comparison Axibase vs. Dgraph vs. Rockset vs. SAP HANA vs. Vertica

Editorial information provided by DB-Engines

Name

Description

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

Distributed and scalable native Graph DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

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

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

Column oriented

Secondary database models

Relational DBMS
Search engine

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

axibase.com/docs/atsd/finance

dgraph.io

rockset.com

www.sap.com/products/hana.html

www.vertica.com

Technical documentation

dgraph.io/docs

docs.rockset.com

help.sap.com/hana

vertica.com/documentation

Developer

Axibase Corporation

Dgraph Labs, Inc.

Rockset

SAP

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2013

2016

2019

2010

2005

Current release

15585

2.0 SPS07 (April 4, 2023), April 2023

12.0.3, January 2023

License

Commercial or Open Source

commercial

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

Open Source

Apache 2.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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

C++

Server operating systems

Linux

Linux
OS X
Windows

hosted

Appliance or cloud-service

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

dynamic 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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

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

SQL

Support of SQL

SQL-like query language

Read-only SQL queries, including JOINs

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

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

HTTP REST

JDBC
ODBC

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++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

SQLScript, R

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Automatic sharding

yes

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication via Raft

yes

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

Eventual Consistency

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

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

Planned for future releases

Access rights for users and organizations can be defined via Rockset console

yes

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing models

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