DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. Hawkular Metrics vs. LeanXcale vs. Netezza vs. RavenDB

System Properties Comparison Apache Impala vs. Hawkular Metrics vs. LeanXcale vs. Netezza vs. RavenDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonLeanXcale  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesData warehouse and analytics appliance part of IBM PureSystemsOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSTime Series DBMSKey-value store
Relational DBMS
Relational DBMSDocument store
Secondary database modelsDocument storeGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websiteimpala.apache.orgwww.hawkular.orgwww.leanxcale.comwww.ibm.com/­products/­netezzaravendb.net
Technical documentationimpala.apache.org/­impala-docs.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guideravendb.net/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCommunity supported by Red HatLeanXcaleIBMHibernating Rhinos
Initial release20132014201520002010
Current release4.1.0, June 20225.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialcommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC#
Server operating systemsLinuxLinux
OS X
Windows
Linux infoincluded in applianceLinux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infothrough Apache DerbyyesSQL-like query language (RQL)
APIs and other access methodsJDBC
ODBC
HTTP RESTJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
OLE DB
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
Python
Ruby
C
Java
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesyes
Triggersnoyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infobased on CassandraSource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoUsers with fine-grained authorization conceptAuthorization levels configured per client per database

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaHawkular MetricsLeanXcaleNetezza infoAlso called PureData System for Analytics by IBMRavenDB
Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

Roundup: Telehouse, Cloudera, Netezza, EMC
31 May 2024, Data Center Knowledge

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, ibm.com

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime | Amazon Web Services
21 August 2019, AWS Blog

Netezza Performance Server
12 August 2020, ibm.com

provided by Google News

RavenDB Launches Version 6.0 Lightning Fast Queries, Data Integrations, Corax Indexing Engine, and Sharding
3 October 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

RavenDB Adds Graph Queries
15 May 2019, Datanami

RavenDB Welcomes David Baruc as Chief Revenue Officer: Seasoned Tech Leader to Drive Global Sales and ...
13 June 2023, PR Newswire

Review: NoSQL database RavenDB
20 March 2019, TechGenix

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here