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. EJDB vs. HBase vs. Manticore Search vs. Vitess

System Properties Comparison Apache Impala vs. EJDB vs. HBase vs. Manticore Search vs. Vitess

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEJDB  Xexclude from comparisonHBase  Xexclude from comparisonManticore Search  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Wide-column store based on Apache Hadoop and on concepts of BigTableMulti-storage database for search, including full-text search.Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSDocument storeWide column storeSearch engineRelational DBMS
Secondary database modelsDocument storeTime Series DBMS infousing the Manticore Columnar LibraryDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.22
Rank#312  Overall
#21  Search engines
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websiteimpala.apache.orggithub.com/­Softmotions/­ejdbhbase.apache.orgmanticoresearch.comvitess.io
Technical documentationimpala.apache.org/­impala-docs.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdhbase.apache.org/­book.htmlmanual.manticoresearch.comvitess.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSoftmotionsApache Software Foundation infoApache top-level project, originally developed by PowersetManticore SoftwareThe Linux Foundation, PlanetScale
Initial release20132012200820172013
Current release4.1.0, June 20222.3.4, January 20216.0, February 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPLv2Open Source infoApache version 2Open Source infoGPL version 2Open Source infoApache Version 2.0, commercial licenses 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++CJavaC++Go
Server operating systemsLinuxserver-lessLinux
Unix
Windows infousing Cygwin
FreeBSD
Linux
macOS
Windows
Docker
Linux
macOS
Data schemeyesschema-freeschema-free, schema definition possibleFixed schemayes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idoptions to bring your own types, AVROInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.nonoCan index from XML
Secondary indexesyesnonoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL-like query languageyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
in-process shared libraryJava API
RESTful HTTP API
Thrift
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoCoprocessors in Javauser defined functionsyes infoproprietary syntax
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication
Source-replica replication
Synchronous replication based on Galera libraryMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoSingle row ACID (across millions of columns)yes infoisolated transactions for atomic changes and binary logging for safe writesACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoUsers with fine-grained authorization concept infono user groups or roles

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 ImpalaEJDBHBaseManticore SearchVitess
DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021,  Krishna Maheshwari (sponsor) 

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

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

StarRocks Brings Speedy OLAP Database to the Cloud
14 July 2022, 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

provided by Google News

Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ...
9 October 2023, AWS Blog

Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase
20 October 2023, hackernoon.com

HBase: The database big data left behind
6 May 2016, InfoWorld

HydraBase – The evolution of HBase@Facebook
5 June 2014, Facebook Engineering

HBase Tutorial
24 February 2023, Simplilearn

provided by Google News

Integrating Manticore Search with Apache Superset
8 August 2023, hackernoon.com

Clickhouse vs Elasticsearch vs Manticore Search Query Times With a 1.7B NYC Taxi Rides Benchmark
1 June 2022, hackernoon.com

Google's Gemini comes to databases
9 April 2024, Yahoo Canada Shine On

Comparing Meilisearch and Manticore Search Using Key Benchmarks
2 May 2023, hackernoon.com

8 Google Alternatives: How to Search Crypto, the Dark Web, More
1 February 2023, Gizmodo

provided by Google News

Vitess, the database clustering system powering YouTube, graduates CNCF incubation
5 November 2019, SiliconANGLE News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

The ultimate MySQL database platform — PlanetScale
20 June 2018, planetscale.com

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube — now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

provided by Google News



Share this page

Featured Products

Milvus logo

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

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

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.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Present your product here