DBMS > ClickHouse vs. GeoMesa vs. Heroic vs. HugeGraph vs. SAP Advantage Database Server

System Properties Comparison ClickHouse vs. GeoMesa vs. Heroic vs. HugeGraph vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

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

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A fast-speed and highly-scalable Graph DBMS

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

Primary database model

Secondary database models

Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

clickhouse.com

www.geomesa.org

github.com/spotify/heroic

github.com/hugegraph
hugegraph.apache.org

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

Technical documentation

clickhouse.com/docs

www.geomesa.org/documentation/stable/user/index.html

spotify.github.io/heroic

hugegraph.apache.org/docs

Developer

Clickhouse Inc.

CCRi and others

Spotify

Baidu

Sybase, SAP

Initial release

2016

2014

2018

1993

Current release

v24.4.1.2088-stable, May 2024

5.0.0, May 2024

0.9

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Scala

Java

Server operating systems

FreeBSD
Linux
macOS

Linux
macOS
Unix

Linux
Windows

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

via Elasticsearch

yes

also supports composite index and range index

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

Groovy
Java
Python

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

depending on storage layer

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

depending on storage layer

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

depending on storage layer

yes

caching of (temporary) tables can be configured

User concepts

Access control

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

yes

depending on the DBMS used for storage

Users, roles and permissions

fine grained access rights according to SQL-standard

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.