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Sentiment analysis and opinion mining is closely coupled with each other. An extensive research work is being carried out in these areas by using different methodologies. Sentiments in a given text are identified by these methodologies as either positive, negative or neutral. Tweets, facebook posts, user comments about certain topics and reviews regarding product, software and movies can be the good source of information. Sentiment Analysis techniques can be used on such data by businesses executives for future planning and forecasting. As the data is obtained from multiple sources and it depends directly on the user which can be from any part of the world so the noisiness in data is a common issue such as mistake in spellings, grammatical errors and improper punctuation. Different approaches are available for sentiment analysis which can automatically sort and categorize the data. These approaches are mainly categorized as Machine Learning based, Lexicon based and Hybrid. A hybrid approach is the combination of machine learning and lexicon based approach for the optimum results, this approach generally yields better results. In this research work different hybrid techniques and tools have been discussed and analyzed from different aspects.