DBMS > GeoSpock vs. Microsoft Azure Data Explorer vs. Oracle vs. TigerGraph vs. VelocityDB

System Properties Comparison GeoSpock vs. Microsoft Azure Data Explorer vs. Oracle vs. TigerGraph vs. VelocityDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Fully managed big data interactive analytics platform

Widely used RDBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

column oriented

Relational DBMS

Graph DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Time Series DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

geospock.com

azure.microsoft.com/services/data-explorer

www.oracle.com/database

www.tigergraph.com

velocitydb.com

Technical documentation

docs.microsoft.com/en-us/azure/data-explorer

docs.oracle.com/en/database

docs.tigergraph.com

velocitydb.com/UserGuide

Developer

GeoSpock

Microsoft

Oracle

VelocityDB Inc

Initial release

2019

1980

2017

2011

Current release

2.0, September 2019

cloud service with continuous releases

23c, September 2023

7.x

License

Commercial or Open Source

commercial

restricted free version is 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

Java, Javascript

C and C++

C++

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Any that supports .NET

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

temporal, categorical

all fields are automatically indexed

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

SQL-like query language (GSQL)

APIs and other access methods

JDBC

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

.Net

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C++
Java

.Net

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Access rights for users can be defined per table

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

Role-based access control

Based on Windows Authentication

More information provided by the system vendor

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.